In this paper, we propose a simultaneous approach to incorporate inventory control decisions––such as economic order quantity and safety stock decisions––into typical facility location models, which are used to solve the distribution... more
In this paper, we propose a simultaneous approach to incorporate inventory control decisions––such as economic order quantity and safety stock decisions––into typical facility location models, which are used to solve the distribution network design problem. A simultaneous model is developed considering a stochastic demand, modeling also the risk pooling phenomenon. We present a non-linear-mixed-integer model and a heuristic solution approach, based on Lagrangian relaxation and the sub-gradient method. In a numerical application, we found that the potential cost reduction, compared to the traditional approach, increases when the holding costs and/or the variability of demand are higher.
HEURISTICS and PROBLEM-SOLVING (VOLUME 2) This section or chapter two. Because of its length I decided to create a second Volume 2. HEURISTICS AND PROBLEMSOLVING (Volume 2) This volume deals with details of heuristic... more
HEURISTICS and PROBLEM-SOLVING (VOLUME 2) This section or chapter two. Because of its length I decided to create a second Volume 2. HEURISTICS AND PROBLEMSOLVING (Volume 2)
This volume deals with details of heuristic approaches and the infinite aspects and features of ‘problem-solving’ and related issues.
The author of the first article I quote suggests that the heuristic tools or devices he mentions will enable individuals to produce philosophy. He seems to think that this idea is one of the major factors that leads to the creation of philosophy.
I wish to indicate, by citations, that there is much, much more to heuristics then the list of heuristics he suggests.
I place the use of heuristic devices in the larger context of problem-solving. The solving of problems is of course merely one aspect of a much larger process that consist of many other features, steps and stages.
The aim of that section and citations are to to make individuals aware of the many aspects of the process of problem conceptualization, investigation and solving or dissolving. I think it is is essential to be aware of these features of problem investigation because without such knowledge and understanding philosophers will suffer from an even greate lack of meta-cognition of the socio-cultural practice of philosophy and the doing of philosophy and of self- metacognition.
The context is online grocery shopping and the paper focuses on the optimization of the related transport logistics that can lead to important economic and environmental advantages. At the beginning of the day, each customer provides: a... more
The context is online grocery shopping and the paper focuses on the optimization of the related transport logistics that can lead to important economic and environmental advantages. At the beginning of the day, each customer provides: a shopping list, defining the product typologies and the related quantities to be collected from the different shops, the delivery address and the related delivery time window. One vehicle is in charge of serving all the customers by collecting the products from the shops and by delivering them to the provided delivery addresses. The target is to find the shortest path that satisfies the customer's needs. The proposed routing algorithms could support also logistic processes in supermarket supply. Each supermarket defines the daily freight demand, in terms of product typologies and related quantities, to be collected from the different manufactures/distributors, the delivery address and the related delivery time window. One vehicle is in charge of collecting the products from manufactures/distributors and of delivering them to the provided delivery addresses. The faced problem is therefore a complex multi commodity pickup and delivery traveling salesman problem. Many constraints could be taken into account, related, for instance, to ecology and customer satisfaction. One local and four global optimization algorithms are proposed; their advantages and limits are discussed. The algorithms are tested on a basic logistic example, the numerical results are reported. The proposed algorithms use effective and efficient optimization algorithms able to minimize the overall miles necessary to deliver the goods in order to increase business efficiency.
The context is online grocery shopping and the paper focuses on the optimization of the related transport logistics that can lead to important economic and environmental advantages. At the beginning of the day, each customer provides: a... more
The context is online grocery shopping and the paper focuses on the optimization of the related transport logistics that can lead to important economic and environmental advantages. At the beginning of the day, each customer provides: a shopping list, defining the product typologies and the related quantities to be collected from the different shops, the delivery address and the related delivery time window. One vehicle is in charge of serving all the customers by collecting the products from the shops and by delivering them to the provided delivery addresses. The target is to find the shortest path that satisfies the customer's needs. The proposed routing algorithms could support also logistic processes in supermarket supply. Each supermarket defines the daily freight demand, in terms of product typologies and related quantities, to be collected from the different manufactures/distributors, the delivery address and the related delivery time window. One vehicle is in charge of collecting the products from manufactures/distributors and of delivering them to the provided delivery addresses. The faced problem is therefore a complex multi commodity pickup and delivery traveling salesman problem. Many constraints could be taken into account, related, for instance, to ecology and customer satisfaction. One local and four global optimization algorithms are proposed; their advantages and limits are discussed. The algorithms are tested on a basic logistic example, the numerical results are reported. The proposed algorithms use effective and efficient optimization algorithms able to minimize the overall miles necessary to deliver the goods in order to increase business efficiency.
Sustainable construction aims at reducing the environmental impact of buildings on human health and natural environment by efficiently using energy, resources and reducing waste and pollution. Building construction has the capacity to... more
Sustainable construction aims at reducing the environmental impact of buildings on human health and natural environment by efficiently using energy, resources and reducing waste and pollution. Building construction has the capacity to make a major contribution to a more sustainable future of our World because this industry is one of the largest contributors to global warming. The use of cold-formed steel framing in construction industry provides sustainable construction which requires less material to carry the same load compare to other materials and reduces amount of waste material at a site. In this study five optimum design algorithms are developed for cold-formed steel frames made of thin-walled sections using the recent metaheuristic techniques. The algorithms considered are firefly, cuckoo search, artificial bee colony with levy flight, biogeography-based optimization and teaching-learning-based optimization algorithms. The design algorithms select the cold-formed thin-walled C-sections listed in AISI-LRFD (American Iron and Steel Institution, Load and Resistance Factor Design) in such a way that the design constraints specified by the code are satisfied and the weight of the steel frame is the minimum. A real size cold-formed steel building is optimized by using each of these algorithms and their performance in attaining the optimum designs is compared.
"Consideramos el problema de localización y ruteo con flota heterogénea (LRPH, por sus siglas en inglés), en el cual se busca determinar los depósitos a ser abiertos, los clientes a ser asignados a cada depósito, y las rutas a ser... more
"Consideramos el problema de localización y ruteo con flota heterogénea (LRPH, por sus siglas en inglés), en el cual se busca determinar los depósitos a ser abiertos, los clientes a ser asignados a cada depósito, y las rutas a ser construidas para satisfacer las demandas de los clientes, considerando una flota de vehículos con capacidad diversa y costos de utilización asociados. El objetivo es minimizar la suma de los costos asociados con la apertura de depósitos, los costos de los vehículos utilizados, y los costos variables directamente relacionados con las distancias recorridas. En este artículo, se propone un algoritmo metaheurístico basado en una búsqueda tabú granular para la resolución del problema. Experimentos computacionales en instancias adaptadas de la literatura, muestran que el algoritmo propuesto es capaz de obtener, en tiempos computacionales razonables, soluciones de alta calidad demostrando su efectividad.
Monitoring a set of targets and extending network lifetime is a critical issue in wireless sensor networks (WSNs). Various coverage scheduling algorithms have been proposed in the literature for monitoring deployed targets in WSNs. These... more
Monitoring a set of targets and extending network lifetime is a critical issue in wireless sensor networks (WSNs). Various coverage scheduling algorithms have been proposed in the literature for monitoring deployed targets in WSNs. These algorithms divide the sensor nodes into cover sets, and each cover set can monitor all targets. It is proven that finding the maximum number of disjointed cover sets is an NP-complete problem. In this paper we present a novel and efficient cover set algorithm based on Imperialist Competitive Algorithm (ICA). The proposed algorithm taking advantage of ICA determines the sensor nodes that must be selected in different cover sets. As the presented algorithm proceeds, the cover sets are generated to monitor all deployed targets. In order to evaluate the performance of the proposed algorithm, several simulations have been conducted and the obtained results show that the proposed approach outperforms similar algorithms in terms of extending the network lifetime. Also, our proposed algorithm has a coverage redundancy that is about 1–2 % close to the optimal value.
Feature selection is one of the issues that have been raised in the discussion of machine learning and statistical identification model. We have provided definitions for feature selection and definitions needed to understand this issue,... more
Feature selection is one of the issues that have been raised in the discussion of machine learning and statistical identification model. We have provided definitions for feature selection and definitions needed to understand this issue, we check. Then, different methods for this problem were based on the type of product, as well as how to evaluate candidate subsets of features, we classify the following categories. As in previous studies may not have understood that different methods of assessment data into consideration, we propose a new approach for assessing similarity of data to understand the relationship between diversity and stability of the data is selected. After review and meta-heuristic algorithms to implement the algorithm found that the cluster algorithm has better performance compared with other algorithms for feature selection sustained.
In this paper we analyze the cryptanalysis of the simplified data encryption standard algorithm using meta-heuristics and in particular genetic algorithms. The classic fitness function when using such an algorithm is to compare n-gram... more
In this paper we analyze the cryptanalysis of the simplified data encryption standard algorithm using meta-heuristics and in particular genetic algorithms. The classic fitness function when using such an algorithm is to compare n-gram statistics of a the decrypted message with those of the target message. We show that using such a function is irrelevant in case of Genetic Algorithm, simply because there is no correlation between the distance to the real key (the optimum) and the value of the fitness, in other words, there is no hidden gradient. In order to emphasize this assumption we experimentally show that a genetic algorithm perform worse than a random search on the cryptanalysis of the simplified data encryption standard algorithm.
The proposed approach avoids the semantic gap in image retrieval by combining automatic relevance feedback and a modified stochastic algorithm. A visual feature database is constructed from the image database, using combined feature... more
The proposed approach avoids the semantic gap in image retrieval by combining automatic relevance feedback and a modified stochastic algorithm. A visual feature database is constructed from the image database, using combined feature vector. Very few fast-computable features are included in this step. The user selects the query image, and based on that, the system ranks the whole dataset. The nearest images are retrieved and the first automatic relevance feedback is generated. The combined similarity of textual and visual feature space using Latent Semantic Indexing is evaluated and the images are labelled as relevant or irrelevant. The feedback drives a feature re-weighting process and is routed to the particle swarm optimizer. Instead of classical swarm update approach, the swarm is split, for each swarm to perform the search in parallel, thereby increasing the performance of the system. It provides a powerful optimization tool and an effective space exploration mechanism. The proposed approach aims to achieve the following goals without any human interaction-to cluster relevant images using meta-heuristics and to dynamically modify the feature space by feeding automatic relevance feedback.
ABSTRACT Monitoring a set of targets and extending network lifetime is a critical issue in wireless sensor networks (WSNs). Various coverage scheduling algorithms have been proposed in the literature for monitoring deployed targets in... more
ABSTRACT Monitoring a set of targets and extending network lifetime is a critical issue in wireless sensor networks (WSNs). Various coverage scheduling algorithms have been proposed in the literature for monitoring deployed targets in WSNs. These algorithms divide the sensor nodes into cover sets, and each cover set can monitor all targets. It is proven that finding the maximum number of disjointed cover sets is an NP-complete problem. In this paper we present a novel and efficient cover set algorithm based on Imperialist Competitive Algorithm (ICA). The proposed algorithm taking advantage of ICA determines the sensor nodes that must be selected in different cover sets. As the presented algorithm proceeds, the cover sets are generated to monitor all deployed targets. In order to evaluate the performance of the proposed algorithm, several simulations have been conducted and the obtained results show that the proposed approach outperforms similar algorithms in terms of extending the network lifetime. Also, our proposed algorithm has a coverage redundancy that is about 1–2 % close to the optimal value.
This article is based on the application of heuristic algorithms to solve the optimum solution for a VLSI circuit. The idea is to find the optimum layout for a 2-to-1 multiplexer with minimal average power. The objective function is the... more
This article is based on the application of heuristic algorithms to solve the optimum solution for a VLSI circuit. The idea is to find the optimum layout for a 2-to-1 multiplexer with minimal average power. The objective function is the average power of 2:1 MUX with four MOSFETs with different channel widths. They make a four dimensional space which is searched by search agents of algorithm. Motivated by the convergence of Invasive Weeds Optimization (IWO) and Genetic Algorithm (GA) and the link of MATLAB with HSPICE Software the optimized layout of 2:1 MUX is obtained. Based on IWO, Fuzzy-IWO, GA, Fuzzy-GA algorithms the best resulting of MUX layout in Static NMOS Logic in 0.18µm Technology with supply voltage of 5v has the average power consumption of 3.6 nW with Fuzzy-IWO.
This article is based on the application of heuristic algorithms to solve the optimum solution for a VLSI circuit. The idea is to find the optimum layout for a 2-to-1 multiplexer with minimal average power. The objective function is the... more
This article is based on the application of heuristic algorithms to solve the optimum solution for a VLSI circuit. The idea is to find the optimum layout for a 2-to-1 multiplexer with minimal average power. The objective function is the average power of 2:1 MUX with four MOSFETs with different channel widths. They make a four dimensional space which is searched by search agents of algorithm. Motivated by the convergence of Invasive Weeds Optimization (IWO) and Genetic Algorithm (GA) and the link of MATLAB with HSPICE Software the optimized layout of 2:1 MUX is obtained. Based on IWO, Fuzzy-IWO, GA, Fuzzy-GA algorithms the best resulting of MUX layout in Static NMOS Logic in 0.18µm Technology with supply voltage of 5v has the average power consumption of 3.6 nW with Fuzzy-IWO.
