Vaccines and refrigerated trucks are critical resources for controlling the spread of epidemic di... more Vaccines and refrigerated trucks are critical resources for controlling the spread of epidemic diseases. This paper addresses a novel bi-objective vehicle routing problem to distribute vaccines among different regions to control the spread of communicable diseases in the aftermath of a disaster. The developed model aims to minimize the social cost incurred by considering different priority groups under the SIR epidemic model and the cost of vehicles used simultaneously. A hybrid solution procedure is developed using the weighted augmented-constraint method, optimal control theory, and dynamic programming. To evaluate the performance of the model and the solution approach, four small test problems and an illustrative example inspired by a real case are presented and their numerical results are discussed.
The vehicle routing problem with backhauls (VRPB) as an extension of the classical vehicle routin... more The vehicle routing problem with backhauls (VRPB) as an extension of the classical vehicle routing problem (VRP) attempts to define a set of routes which services both linehaul customers whom product are to be delivered and backhaul customers whom goods need to be collected. A primary objective for the problem usually is minimizing the total distribution cost. Most real-life problems have other objectives addition to this common primary objective. This paper describes a multi-objective model for VRPB with time windows (VRPBTW) and some new assumptions. We present a goal programming approach and a heuristic algorithm to solve the problem. Computational experiments are carried out and performance of developed methods is discussed.
International Journal of Industrial Engineering & Production Research, 2019
Since customization increases, build-to-order systems have received greater attention from resear... more Since customization increases, build-to-order systems have received greater attention from researchers and practitioners. This paper presents a new build-to-order supply chain model with multiple objectives that minimize the total cost and lead time and, also, maximize the quality level. The model is first formulated in a deterministic condition and, then, the uncertainty of the cost and quality by the scenario-based approach to solving a robust optimization was investigated. The return policy and outsourcing are the new issues in a build-to-order supply chain considering the cost and inventory. A Benders decomposition algorithm is used to solve and validate the model. Finally, the related results are analyzed and compared with the results obtained by CPLEX for deterministic and scenario-based models.
Journal of Humanitarian Logistics and Supply Chain Management, 2021
PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepar... more PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepared to face difficult conditions after a disaster to reduce human casualties and meet the needs of the people. After the disaster, one of the most essential measures is to deliver relief supplies to those affected by the disaster. Therefore, this paper aims to assign demand points to the warehouses as well as routing their related relief vehicles after a disaster considering convergence in the border warehouses.Design/methodology/approachThis research proposes a multi-objective, multi-commodity and multi-period queueing-inventory-routing problem in which a queuing system has been applied to reduce the congestion in the borders of the affected zones. To show the validity of the proposed model, a small-size problem has been solved using exact methods. Moreover, to deal with the complexity of the problem, a metaheuristic algorithm has been utilized to solve the large dimensions of the proble...
Supply chain integration has become one of the most attractive topics for researchers in recent y... more Supply chain integration has become one of the most attractive topics for researchers in recent years. One of the advantages of this integration is in improving overall profit in comparison to separate decisions. In this study, an integrated scheduling and distribution problem is investigated. One of the contributions of this paper is to study this problem from a multi-agent viewpoint. In this case, each agent has a set of jobs with its own objective and compete with each other to acquire supply chain resources. Here, a two-agent problem is discussed where the objectives of the agents are the minimization of the total tardiness and the total cost of distribution. A mathematical formulation and two heuristics based on decomposition approaches are presented. In the first approach, a modified Benders decomposition is presented. Also, some valid inequalities are introduced to increase the convergence speed of this algorithm. In the second approach, a decomposition and cutting approach is developed. The results represent the good performance of both algorithms in comparison to other exact methods.
International Journal of Production Research, 2017
Recent trends in the commercial aviation industry have resulted in rapidly increasing complexity ... more Recent trends in the commercial aviation industry have resulted in rapidly increasing complexity and decentralisation in service parts logistics systems. As a consequence, MRO service providers tend to adopt more flexible strategies, such as service parts sourcing and demand fulfilment for customers with different service-level requirements. The MRO service providers often enter into cooperative agreements with other service providers to pool inventories, enabling them to increase their flexibility in delivering services to multiple airlines with different contractual terms. Although using cooperative strategies, such as emergency resupply, is useful to increase flexibility, the inherent complexity of optimal mechanism is a critical issue that needs to be further investigated. To this aim, we consider a repairable service parts inventory system with multi-customer classes and develop an optimal emergency resupply policy. Following this, to overcome the intractability issue of finding the optimal policy, an efficient approximation method is proposed. Numerical results indicate that the proposed approximation method is highly accurate, and leads to a significant costs reduction. This paper sheds light on the effectiveness of emergency resupply policy that improves MRO service providers’ flexibility and enables them to ensure responsive service parts inventory.
International Journal of Computer Integrated Manufacturing, 2016
This paper explores a no-wait hybrid flow shop scheduling problem (NWHFSSP) with realistic assump... more This paper explores a no-wait hybrid flow shop scheduling problem (NWHFSSP) with realistic assumptions, including unrelated parallel machines at each stage, machine eligibility, sequence-dependent setup times and different ready times, in order to minimise the mean tardiness. The largest position value rule is proposed to transmute continuous vectors of each solution into job permutations. Also, a novel biogeography-based optimisation (BBO) algorithm is developed to solve the aforementioned problem. To evaluate the effect of various parameters on the performance of the proposed BBO algorithm, response surface methodology (RSM) is employed. Production scenarios for small-scale and large-scale problems are created and tested for the validation purposes. Computational experiment results indicate that the proposed BBO outperforms all of the tested algorithms in terms of four measures, namely, mean relative percentage deviation (RPD), standard deviation of RPD, best RPD and worst RPD. It is shown that BBO produces the best solutions among the tested algorithms in terms of not only the four RPD measures but also computation time.
Process Integration and Optimization for Sustainability, 2021
This paper aims to develop a sustainable closed-loop supply chain network model with a modular si... more This paper aims to develop a sustainable closed-loop supply chain network model with a modular single product which is specifically designed for the automotive industry. Drawing upon sustainability criteria, three objective functions are formulated for the closed-loop network design problem including maximizing total profit across the network, minimizing the effects of environmental pollutants and maximizing employments created by the establishment of the required facilities and also maximizing the weighted sum of the minimum distance of facilities from the residential areas. In order to validate the research, a case study of the Iran’s automotive industry is also conducted. In addition, a scenario-based approach which applies the stochastic programming is used to cope with the uncertainty in both the demand and the amount of returned unusable vehicles. The results show that the stochastic programming approach is successful in mitigating the effects of uncertainties. Moreover, augmented $$\varepsilon$$ ε -constraint methods are applied to deal with the proposed model. The preferred Pareto optimal solution achieves a 55.1% decrease in the environmental objective value, with only 0.2% increase in the economic objective value relative to the corresponding optimal value.
The vehicle routing and scheduling problem with crossdocking for perishable products under uncert... more The vehicle routing and scheduling problem with crossdocking for perishable products under uncertainty: Two robust bi-objective models, Applied Mathematical Modelling (2019), doi:
One of the patients' basic needs when referring to the hospital is to access doctors as soon as p... more One of the patients' basic needs when referring to the hospital is to access doctors as soon as possible at a low cost. In this regard, many hospital managers aim to improve healthcare quality. They strive to plan and perform better patient flow in different parts of hospitals. With the widespread of Covid-19, the importance of this matter has become more apparent. Queueing systems are one of the methods that help recognize delays and help to identify bottlenecks. This paper has extended a queue theory model to measure the number of servers in each part of the hospital. The model aims to reduce the hospital's expected total cost, including the waiting time cost of the patients in queues, idle server cost, operating, and the marginal cost of the servers, in a covid-19 pandemic. The proposed model has been solved with Grasshopper Optimization Algorithm (GOA) for large-scale data. Then sensitivity analysis is presented to understand the model better and identify effective parameters.
Objective: The present work proposes a mathematical model for a four-echelon supply chain network... more Objective: The present work proposes a mathematical model for a four-echelon supply chain network for a seasonal product with stochastic demand. The supply chain structure includes a supplier, a producer, a distributor, and a retailer with three sale channels. Methods: The methodology introduced in this paper is a fundamental yet practical one that expands the knowledge of modeling for omnichannel supply chain and examines the outcomes in a real case study using a quantitative approach. In this case study, the retailer and the distributor are decision-makers, who decide the optimum order quantity. First, the centralized and decentralized models are identified. Second, the optimum order quantity for each model is determined, and finally, the results are verified using a numerical approach. Further, a sensitivity analysis is performed on the parameters that affect the profits obtained by members and the supply chain. Results: Numerical examples show that the supply chain profit in the...
This paper presents a multi-product, multi-period inventory problem in an uncertain environment w... more This paper presents a multi-product, multi-period inventory problem in an uncertain environment where the main suppliers are prone to yield uncertainty. In order to overcome the arisen uncertainties, two basic approaches of emergency ordering and product substitutability are taken into consideration. In the proposed emergency ordering scheme, two sets of suppliers, i.e. cheap unreliable and expensive reliable (emergency) suppliers, are considered and a tradeo between the cheap price of the main suppliers and reliability of emergency supplier is attained. In product substitution scheme, the demand of each product is ful lled directly by the related product or other substitute products. A riskaverse decision maker is taken into consideration whose risk-averseness level is controlled by the portion of demand which should be de nitely satis ed and not backordered or lost. A robust optimization approach with two variability measures is proposed to minimize the variability of the model. The results reveal the value of emergency ordering and product substitution. In addition, the results suggest which measure should be selected according to the decision maker's attitude toward the desired pro t, variability, and service level.
The location routing problem (LRP), automatic guided vehicle (AGV), and uncertainty planner facil... more The location routing problem (LRP), automatic guided vehicle (AGV), and uncertainty planner facility (UPF) in facility location problems (FLP) have been critical. This research proposed the role of LRP in intelligence AGV location–routing problem (IALRP) and energy-consuming impact in CMS. The goal of problem minimization dispatching opening cost and the cost of AGV trucking. We set up multi-objective programming. To solve the model, we utilized and investigate the imperialist competitor algorithm (ICA) with variable neighborhood search (VNS). It is shown that the ICAVNS algorithm is high quality effects for the integrated LRP in AGVs and comparison, with the last researches, the sensitivity analysis, and numerical examples imply the validity and good convexity of the purposed model according to the cost minimization.
Journal of Industrial and Systems Engineering, 2018
Co-firing biomass plants are of extensive demand due to utilization of both agricultural residues... more Co-firing biomass plants are of extensive demand due to utilization of both agricultural residues (main) and natural gas (stand-by). Researchers have shown that one strategic decision in establishment of agricultural residues based plants, is location optimization problem. Moreover, mismatch between agricultural lands and biomass plants can lead to high transportation costs and related carbon dioxide emissions. Standard indicators are considered and used for the stated multi-objective mathematical problem. This article presents a novel approach based on Z-number data envelopment analysis (DEA) model to handle severe uncertainty associated with actual data. The multi-objective mathematical model considers environmental, economic and social aspects of biomass plants. Moreover, fuzzy DEA model is utilized to verify and validate the results of Z-number DEA model through 30 independent experiments. The obtained results indicate that “accessibility to water”, “population”, “cost of land”,...
Today with the outbreak of the COVID-19 many people prefer to stay home and buy their required pr... more Today with the outbreak of the COVID-19 many people prefer to stay home and buy their required products from online sellers and receive them in their home or office at their desired times. This change has increased the workload of online retailers. In an online retailing system, lots of orders containing different products arrive dynamically and must be delivered in the due dates requested by customers, so there is a limited time to retrieve products from their storage locations, pack them, load them on trucks, and deliver to their destinations. In this study, we deal with the integrated order batching and delivery planning of an online retailer that stores a variety of products in a warehouse and sells them online. A mixed-integer nonlinear programming model is proposed that decides on order batching, scheduling of batches, assigning orders to trucks, and scheduling and routing of trucks simultaneously in an offline setting. This model clarifies the domain of the problem and its co...
We propose an enhanced multi-objective harmony search (EMOHS) algorithm and a Gaussian mutation t... more We propose an enhanced multi-objective harmony search (EMOHS) algorithm and a Gaussian mutation to solve the flexible flow shop scheduling problems with sequence-based setup time, transportation time, and probable rework. A constructive heuristic is used to generate the initial solution, and clustering is applied to improve the solution. The proposed algorithm uses response surface methodology to minimize both maximum completion time and mean tardiness, concurrently. We evaluate the efficacy of the proposed algorithm using computational experiments based on five measures of diversity metric, simultaneous rate of achievement for two objectives, mean ideal distance, quality metric, and coverage. The experimental results demonstrate the effectiveness of the proposed EMOHS compared with the existing algorithms for solving multi-objective problems. c
International Journal of Logistics Systems and Management, 2015
Although disruption risks may occur with a low probability in a supply chain network, they have n... more Although disruption risks may occur with a low probability in a supply chain network, they have negative financial impacts and also the recovery process from their destructive effects is very slow. This paper proposes a reliability model for an integrated forward-reverse logistics network design, which can cope with both partial and complete facility disruptions. The reliability model is formulated as a stochastic robust programming whose objective function is to minimise the fixed opening costs of facilities and the expected cost of disruption scenarios, including processing costs, transportation costs, and penalty costs for non-satisfied demands. For doing so, a recent robust optimisation approach is modified to protect the concerned network against partial and complete capacity disruptions. Furthermore, a stochastic programming is employed to account for all interested scenarios. Three numerical experiments are designed to study the effect of capacity disruptions on the concerned logistic network. Finally, the results of the proposed model are compared with the conventional robust optimisation models.
Vaccines and refrigerated trucks are critical resources for controlling the spread of epidemic di... more Vaccines and refrigerated trucks are critical resources for controlling the spread of epidemic diseases. This paper addresses a novel bi-objective vehicle routing problem to distribute vaccines among different regions to control the spread of communicable diseases in the aftermath of a disaster. The developed model aims to minimize the social cost incurred by considering different priority groups under the SIR epidemic model and the cost of vehicles used simultaneously. A hybrid solution procedure is developed using the weighted augmented-constraint method, optimal control theory, and dynamic programming. To evaluate the performance of the model and the solution approach, four small test problems and an illustrative example inspired by a real case are presented and their numerical results are discussed.
The vehicle routing problem with backhauls (VRPB) as an extension of the classical vehicle routin... more The vehicle routing problem with backhauls (VRPB) as an extension of the classical vehicle routing problem (VRP) attempts to define a set of routes which services both linehaul customers whom product are to be delivered and backhaul customers whom goods need to be collected. A primary objective for the problem usually is minimizing the total distribution cost. Most real-life problems have other objectives addition to this common primary objective. This paper describes a multi-objective model for VRPB with time windows (VRPBTW) and some new assumptions. We present a goal programming approach and a heuristic algorithm to solve the problem. Computational experiments are carried out and performance of developed methods is discussed.
International Journal of Industrial Engineering & Production Research, 2019
Since customization increases, build-to-order systems have received greater attention from resear... more Since customization increases, build-to-order systems have received greater attention from researchers and practitioners. This paper presents a new build-to-order supply chain model with multiple objectives that minimize the total cost and lead time and, also, maximize the quality level. The model is first formulated in a deterministic condition and, then, the uncertainty of the cost and quality by the scenario-based approach to solving a robust optimization was investigated. The return policy and outsourcing are the new issues in a build-to-order supply chain considering the cost and inventory. A Benders decomposition algorithm is used to solve and validate the model. Finally, the related results are analyzed and compared with the results obtained by CPLEX for deterministic and scenario-based models.
Journal of Humanitarian Logistics and Supply Chain Management, 2021
PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepar... more PurposeDue to the randomness and unpredictability of many disasters, it is essential to be prepared to face difficult conditions after a disaster to reduce human casualties and meet the needs of the people. After the disaster, one of the most essential measures is to deliver relief supplies to those affected by the disaster. Therefore, this paper aims to assign demand points to the warehouses as well as routing their related relief vehicles after a disaster considering convergence in the border warehouses.Design/methodology/approachThis research proposes a multi-objective, multi-commodity and multi-period queueing-inventory-routing problem in which a queuing system has been applied to reduce the congestion in the borders of the affected zones. To show the validity of the proposed model, a small-size problem has been solved using exact methods. Moreover, to deal with the complexity of the problem, a metaheuristic algorithm has been utilized to solve the large dimensions of the proble...
Supply chain integration has become one of the most attractive topics for researchers in recent y... more Supply chain integration has become one of the most attractive topics for researchers in recent years. One of the advantages of this integration is in improving overall profit in comparison to separate decisions. In this study, an integrated scheduling and distribution problem is investigated. One of the contributions of this paper is to study this problem from a multi-agent viewpoint. In this case, each agent has a set of jobs with its own objective and compete with each other to acquire supply chain resources. Here, a two-agent problem is discussed where the objectives of the agents are the minimization of the total tardiness and the total cost of distribution. A mathematical formulation and two heuristics based on decomposition approaches are presented. In the first approach, a modified Benders decomposition is presented. Also, some valid inequalities are introduced to increase the convergence speed of this algorithm. In the second approach, a decomposition and cutting approach is developed. The results represent the good performance of both algorithms in comparison to other exact methods.
International Journal of Production Research, 2017
Recent trends in the commercial aviation industry have resulted in rapidly increasing complexity ... more Recent trends in the commercial aviation industry have resulted in rapidly increasing complexity and decentralisation in service parts logistics systems. As a consequence, MRO service providers tend to adopt more flexible strategies, such as service parts sourcing and demand fulfilment for customers with different service-level requirements. The MRO service providers often enter into cooperative agreements with other service providers to pool inventories, enabling them to increase their flexibility in delivering services to multiple airlines with different contractual terms. Although using cooperative strategies, such as emergency resupply, is useful to increase flexibility, the inherent complexity of optimal mechanism is a critical issue that needs to be further investigated. To this aim, we consider a repairable service parts inventory system with multi-customer classes and develop an optimal emergency resupply policy. Following this, to overcome the intractability issue of finding the optimal policy, an efficient approximation method is proposed. Numerical results indicate that the proposed approximation method is highly accurate, and leads to a significant costs reduction. This paper sheds light on the effectiveness of emergency resupply policy that improves MRO service providers’ flexibility and enables them to ensure responsive service parts inventory.
International Journal of Computer Integrated Manufacturing, 2016
This paper explores a no-wait hybrid flow shop scheduling problem (NWHFSSP) with realistic assump... more This paper explores a no-wait hybrid flow shop scheduling problem (NWHFSSP) with realistic assumptions, including unrelated parallel machines at each stage, machine eligibility, sequence-dependent setup times and different ready times, in order to minimise the mean tardiness. The largest position value rule is proposed to transmute continuous vectors of each solution into job permutations. Also, a novel biogeography-based optimisation (BBO) algorithm is developed to solve the aforementioned problem. To evaluate the effect of various parameters on the performance of the proposed BBO algorithm, response surface methodology (RSM) is employed. Production scenarios for small-scale and large-scale problems are created and tested for the validation purposes. Computational experiment results indicate that the proposed BBO outperforms all of the tested algorithms in terms of four measures, namely, mean relative percentage deviation (RPD), standard deviation of RPD, best RPD and worst RPD. It is shown that BBO produces the best solutions among the tested algorithms in terms of not only the four RPD measures but also computation time.
Process Integration and Optimization for Sustainability, 2021
This paper aims to develop a sustainable closed-loop supply chain network model with a modular si... more This paper aims to develop a sustainable closed-loop supply chain network model with a modular single product which is specifically designed for the automotive industry. Drawing upon sustainability criteria, three objective functions are formulated for the closed-loop network design problem including maximizing total profit across the network, minimizing the effects of environmental pollutants and maximizing employments created by the establishment of the required facilities and also maximizing the weighted sum of the minimum distance of facilities from the residential areas. In order to validate the research, a case study of the Iran’s automotive industry is also conducted. In addition, a scenario-based approach which applies the stochastic programming is used to cope with the uncertainty in both the demand and the amount of returned unusable vehicles. The results show that the stochastic programming approach is successful in mitigating the effects of uncertainties. Moreover, augmented $$\varepsilon$$ ε -constraint methods are applied to deal with the proposed model. The preferred Pareto optimal solution achieves a 55.1% decrease in the environmental objective value, with only 0.2% increase in the economic objective value relative to the corresponding optimal value.
The vehicle routing and scheduling problem with crossdocking for perishable products under uncert... more The vehicle routing and scheduling problem with crossdocking for perishable products under uncertainty: Two robust bi-objective models, Applied Mathematical Modelling (2019), doi:
One of the patients' basic needs when referring to the hospital is to access doctors as soon as p... more One of the patients' basic needs when referring to the hospital is to access doctors as soon as possible at a low cost. In this regard, many hospital managers aim to improve healthcare quality. They strive to plan and perform better patient flow in different parts of hospitals. With the widespread of Covid-19, the importance of this matter has become more apparent. Queueing systems are one of the methods that help recognize delays and help to identify bottlenecks. This paper has extended a queue theory model to measure the number of servers in each part of the hospital. The model aims to reduce the hospital's expected total cost, including the waiting time cost of the patients in queues, idle server cost, operating, and the marginal cost of the servers, in a covid-19 pandemic. The proposed model has been solved with Grasshopper Optimization Algorithm (GOA) for large-scale data. Then sensitivity analysis is presented to understand the model better and identify effective parameters.
Objective: The present work proposes a mathematical model for a four-echelon supply chain network... more Objective: The present work proposes a mathematical model for a four-echelon supply chain network for a seasonal product with stochastic demand. The supply chain structure includes a supplier, a producer, a distributor, and a retailer with three sale channels. Methods: The methodology introduced in this paper is a fundamental yet practical one that expands the knowledge of modeling for omnichannel supply chain and examines the outcomes in a real case study using a quantitative approach. In this case study, the retailer and the distributor are decision-makers, who decide the optimum order quantity. First, the centralized and decentralized models are identified. Second, the optimum order quantity for each model is determined, and finally, the results are verified using a numerical approach. Further, a sensitivity analysis is performed on the parameters that affect the profits obtained by members and the supply chain. Results: Numerical examples show that the supply chain profit in the...
This paper presents a multi-product, multi-period inventory problem in an uncertain environment w... more This paper presents a multi-product, multi-period inventory problem in an uncertain environment where the main suppliers are prone to yield uncertainty. In order to overcome the arisen uncertainties, two basic approaches of emergency ordering and product substitutability are taken into consideration. In the proposed emergency ordering scheme, two sets of suppliers, i.e. cheap unreliable and expensive reliable (emergency) suppliers, are considered and a tradeo between the cheap price of the main suppliers and reliability of emergency supplier is attained. In product substitution scheme, the demand of each product is ful lled directly by the related product or other substitute products. A riskaverse decision maker is taken into consideration whose risk-averseness level is controlled by the portion of demand which should be de nitely satis ed and not backordered or lost. A robust optimization approach with two variability measures is proposed to minimize the variability of the model. The results reveal the value of emergency ordering and product substitution. In addition, the results suggest which measure should be selected according to the decision maker's attitude toward the desired pro t, variability, and service level.
The location routing problem (LRP), automatic guided vehicle (AGV), and uncertainty planner facil... more The location routing problem (LRP), automatic guided vehicle (AGV), and uncertainty planner facility (UPF) in facility location problems (FLP) have been critical. This research proposed the role of LRP in intelligence AGV location–routing problem (IALRP) and energy-consuming impact in CMS. The goal of problem minimization dispatching opening cost and the cost of AGV trucking. We set up multi-objective programming. To solve the model, we utilized and investigate the imperialist competitor algorithm (ICA) with variable neighborhood search (VNS). It is shown that the ICAVNS algorithm is high quality effects for the integrated LRP in AGVs and comparison, with the last researches, the sensitivity analysis, and numerical examples imply the validity and good convexity of the purposed model according to the cost minimization.
Journal of Industrial and Systems Engineering, 2018
Co-firing biomass plants are of extensive demand due to utilization of both agricultural residues... more Co-firing biomass plants are of extensive demand due to utilization of both agricultural residues (main) and natural gas (stand-by). Researchers have shown that one strategic decision in establishment of agricultural residues based plants, is location optimization problem. Moreover, mismatch between agricultural lands and biomass plants can lead to high transportation costs and related carbon dioxide emissions. Standard indicators are considered and used for the stated multi-objective mathematical problem. This article presents a novel approach based on Z-number data envelopment analysis (DEA) model to handle severe uncertainty associated with actual data. The multi-objective mathematical model considers environmental, economic and social aspects of biomass plants. Moreover, fuzzy DEA model is utilized to verify and validate the results of Z-number DEA model through 30 independent experiments. The obtained results indicate that “accessibility to water”, “population”, “cost of land”,...
Today with the outbreak of the COVID-19 many people prefer to stay home and buy their required pr... more Today with the outbreak of the COVID-19 many people prefer to stay home and buy their required products from online sellers and receive them in their home or office at their desired times. This change has increased the workload of online retailers. In an online retailing system, lots of orders containing different products arrive dynamically and must be delivered in the due dates requested by customers, so there is a limited time to retrieve products from their storage locations, pack them, load them on trucks, and deliver to their destinations. In this study, we deal with the integrated order batching and delivery planning of an online retailer that stores a variety of products in a warehouse and sells them online. A mixed-integer nonlinear programming model is proposed that decides on order batching, scheduling of batches, assigning orders to trucks, and scheduling and routing of trucks simultaneously in an offline setting. This model clarifies the domain of the problem and its co...
We propose an enhanced multi-objective harmony search (EMOHS) algorithm and a Gaussian mutation t... more We propose an enhanced multi-objective harmony search (EMOHS) algorithm and a Gaussian mutation to solve the flexible flow shop scheduling problems with sequence-based setup time, transportation time, and probable rework. A constructive heuristic is used to generate the initial solution, and clustering is applied to improve the solution. The proposed algorithm uses response surface methodology to minimize both maximum completion time and mean tardiness, concurrently. We evaluate the efficacy of the proposed algorithm using computational experiments based on five measures of diversity metric, simultaneous rate of achievement for two objectives, mean ideal distance, quality metric, and coverage. The experimental results demonstrate the effectiveness of the proposed EMOHS compared with the existing algorithms for solving multi-objective problems. c
International Journal of Logistics Systems and Management, 2015
Although disruption risks may occur with a low probability in a supply chain network, they have n... more Although disruption risks may occur with a low probability in a supply chain network, they have negative financial impacts and also the recovery process from their destructive effects is very slow. This paper proposes a reliability model for an integrated forward-reverse logistics network design, which can cope with both partial and complete facility disruptions. The reliability model is formulated as a stochastic robust programming whose objective function is to minimise the fixed opening costs of facilities and the expected cost of disruption scenarios, including processing costs, transportation costs, and penalty costs for non-satisfied demands. For doing so, a recent robust optimisation approach is modified to protect the concerned network against partial and complete capacity disruptions. Furthermore, a stochastic programming is employed to account for all interested scenarios. Three numerical experiments are designed to study the effect of capacity disruptions on the concerned logistic network. Finally, the results of the proposed model are compared with the conventional robust optimisation models.
This paper presents a hybrid memetic algorithm for the problem of scheduling n jobs on m unrelate... more This paper presents a hybrid memetic algorithm for the problem of scheduling n jobs on m unrelated parallel machines with the objective of maximizing the weighted number of jobs that are completed exactly at their due dates. For each job, due date, weight, and the processing times on different machines are given. It has been shown that when the numbers of machines are a part of input, this problem is NP-hard in the strong sense. At first, the problem is formulated as an integer linear programming model. This model is practical to solve small-size problems. Afterward, a hybrid memetic algorithm is implemented which uses two heuristic algorithms as constructive algorithms, making initial population set. A data oriented mutation operator is implemented so as to facilitate memetic algorithm search process. Performance of all algorithms including heuristics (H1 and H2), hybrid genetic algorithm and hybrid memetic algorithm are evaluated through computational experiments which showed the capabilities of the proposed hybrid algorithm.
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Papers by Fariborz Jolai