Most of the construction projects are exposed to time and cost overruns due to various factors and this is a major problem. As a solution to this, the Earned Value Management (EVM) method is considered. EVM is a powerful and well-known... more
Most of the construction projects are exposed to time and cost overruns due to various factors and this is a major problem. As a solution to this, the Earned Value Management (EVM) method is considered. EVM is a powerful and well-known method used in monitoring and controlling the project. EVM gives an early indication that either project is delayed or not and the project is either over budget or under budget at any particular day by tracking it. Thus, it helps to improve the management control system of a construction project, to detect and control the problems in potential risk areas and to suggest the importance and purpose of monitoring the construction work. This paper explains the main parameters of the EVM system involved in the calculation of time and cost for construction projects. In this study, the Primavera P6 software is used to deals with the project monitoring process of a seven-storeyed (G+6) faculty building whose construction is in progress at Istanbul, Turkey. A comparison between the planned progress of construction activities and actual progress is performed and the analysis results are interpreted. This case study justifies the benefits of using EVM for project cash flow analysis and forecasting.
Resource Constrained Project Scheduling Problems (RCPSP), especially their stochastic variants, and the methods operating on them represent a general project scheduling optimization framework. This paper presents the survey of methods and... more
Resource Constrained Project Scheduling Problems (RCPSP), especially their stochastic variants, and the methods operating on them represent a general project scheduling optimization framework. This paper presents the survey of methods and models that are put into the historical context and are categorized according to their working principles. It aims to supplement and update existing RCPSP surveys. The current state of the research field is assessed and potential research venues are identified.
In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic algorithm for solving the resource constrained project scheduling problem (RCPSP). To the best of our knowledge, this is the first attempt to develop a PSO... more
In this paper, we propose a particle swarm optimization (PSO) based hyper-heuristic algorithm for solving the resource constrained project scheduling problem (RCPSP). To the best of our knowledge, this is the first attempt to develop a PSO hyper-heuristic and apply to the classic RCPSP. The hyper-heuristic works as an upper-level algorithm that controls several low-level heuristics which operate to the solution space. The solution representation is based on random keys. Active schedules are constructed by the serial scheduling generation scheme using the priorities of the activities which are modified by the low-level heuristics of the algorithm. Also, the double justification operator, i.e. a forward–backward improvement procedure, is applied to all solutions. The proposed approach was tested on a set of standard problem instances of the well-known library PSPLIB and compared with other approaches from the literature. The promising computational results validate the effectiveness of the proposed approach.
This paper presents a method to minimize the duration of the project using a structured method by defining and evaluating multiple constraints such as precedence constraints, resource constraints and deadline constraints.... more
This paper presents a method to minimize the duration of the project using a structured method by defining and evaluating multiple constraints such as precedence constraints, resource constraints and deadline constraints. Resource-Constrained Project Scheduling Problem (RCPSP) considers resources of limited availability and activities of known durations and resources requests, linked by precedence relations. The problem consists of finding a schedule of minimal duration by assigning a start time to each activity such that the precedence relations and the resource availabilities and deadline constraints are represented. Comparing to classical optimization techniques, meta-heuristic optimization techniques require less time to find the optimal solution for complex problems like RCPSP. Out of several meta-heuristic techniques, Genetic Algorithm is chosen for optimization. In this research, two problems from literature and two real life problems are chosen for time optimization using Genetic Algorithm (GA). All the GA parameters were studied and the optimization is performed using Matrix Laboratory (MATLAB).
The objective the work is intend to highlight the key features and afford finest future directions in the research community of Resource Allocation, Resource Scheduling and Resource management from 2009 to 2016. Exemplifying how research... more
The objective the work is intend to highlight the key features and afford finest future directions in the research community of Resource Allocation, Resource Scheduling and Resource management from 2009 to 2016. Exemplifying how research on Resource Allocation, Resource Scheduling and Resource management has progressively increased in the past decade by inspecting articles, papers from scientific and standard publications. Survey materialized in three fold process. Firstly, investigate on the amalgamation of Resource Allocation, Resource Scheduling and then proceeded with Resource management. Secondly, we performed a structural analysis on different author's prominent contributions in the form of tabulation by categories and graphical representation. Thirdly, huddle with conceptual similarity in the field and also impart a summary on all resource allocations. In cloud computing environments, there are two players: cloud providers and cloud users. On one hand, providers hold massive computing resources in their large datacenters and rent resources out to users on a per-usage basis. On the other hand, there are users who have applications with fluctuating loads and lease resources from providers to run their applications. Further, delivers conclusions by conferring future research directions in the field of cloud computing, such as reduce clouds early in the Internet, combining Resource Allocation, Resource Scheduling and Resource management rather than a Cloud model for providing high quality results, etc.
Resource leveling is used in project scheduling to reduce fluctuation in resource usage over the period of project implementation. Fluctuating resource usage frequently creates the untenable requirement of regularly hiring and firing... more
Resource leveling is used in project scheduling to reduce fluctuation in resource usage over the period of project implementation. Fluctuating resource usage frequently creates the untenable requirement of regularly hiring and firing temporary staff to meet short-term project needs. Construction project decision makers currently rely on experience-based methods to manage fluctuations. However, these methods lack consistency and may result in unnecessary waste of resources or costly schedule overruns. This research introduces a novel discrete symbiotic organisms search for optimizing multiple resources leveling in the multiple projects scheduling problem (DSOS-MRLMP). The optimization model proposed is based on a recently developed metaheuristic algorithm called symbiotic organisms search (SOS). SOS mimics the symbiotic relationship strategies that organisms use to survive in the ecosystem. Experimental results and statistical tests indicate that the proposed model obtains optimal results more reliably and efficiently than do the other optimization algorithms considered. The proposed optimization model is a promising alternative approach to assisting project managers in handling MRLMP effectively.
The resource constrained multi-project scheduling problem (RCMPSP) has predominately been addressed in deterministic environment. Yet, uncertainty is inherent to real-life problems and the rise in adopting projects and portfolios in... more
The resource constrained multi-project scheduling problem (RCMPSP) has predominately been addressed in deterministic environment. Yet, uncertainty is inherent to real-life problems and the rise in adopting projects and portfolios in managing business organizations has initiated growing interest in considering stochastic aspects when developing a resource schedule. Priority rules (PR) is a common approach to solving the RCMPSP avoiding its computational complexity. Since the performance of PRs is highly dependent on project context, it is necessary to study the performance of PRs with real-life cases. The current study presents an application of 17 priority rules to a portfolio of deep-water construction projects. The results confirm previous results obtained from the literature and gives project and portfolio managers insights about the adequacy of different PRs with respect to schedule quality and robustness.
The resource-constrained project scheduling problem (RCPSP) consists of a set of non-preemptive activities that follow precedence relationship and consume resources. Under the limited amount of the resources, the objective of RCPSP is to... more
The resource-constrained project scheduling problem (RCPSP) consists of a set of non-preemptive activities that follow precedence relationship and consume resources. Under the limited amount of the resources, the objective of RCPSP is to find a schedule of the activities to minimize the project makespan. This article presents a new genetic algorithm (GA) by incorporating a local search strategy in GA operators. The local search strategy improves the efficiency of searching the solution space while keeping the randomness of the GA approach. Extensive numerical experiments show that the proposed GA with neighborhood search works well regarding solution quality and computational time compared with existing algorithms in the RCPSP literature, especially for the instances with a large number of activities.
In this note we propose an iterative scheduling technique which consists of consecutive forward/backward scheduling passes aimed at reducing the project duration by smoothing out the project's resource profile. The idea of iterative... more
In this note we propose an iterative scheduling technique which consists of consecutive forward/backward scheduling passes aimed at reducing the project duration by smoothing out the project's resource profile. The idea of iterative scheduling is initiated by Li and Willis in their related paper. The only common point between their scheduling technique and the one proposed here is the iterative feature. The two techniques differ both in algorithmic aspects and in the way activities are selected for scheduling at a decision point. In the technique proposed here activities are evaluated by well-reputed dispatching rules and a conflict based decision-making process called Local Constraint Based Analysis (LCBA). The results on benchmark problems from the literature demonstrate that LCBA specifically exploits the flexible activity time windows provided by the iterative scheduling technique.
This paper presents a new optimization technique called water cycle algorithm (WCA) which is applied to a number of constrained optimization and engineering design problems. The fundamental concepts and ideas which underlie the proposed... more
This paper presents a new optimization technique called water cycle algorithm (WCA) which is applied to a number of constrained optimization and engineering design problems. The fundamental concepts and ideas which underlie the proposed method is inspired from nature and based on the observation of water cycle process and how rivers and streams flow to the sea in the real world. A comparative study has been carried out to show the effectiveness of the WCA over other well-known optimizers in terms of computational effort (measures as number of function evaluations) and function value (accuracy) in this paper.
In this paper, we propose a multi-skill project scheduling problem model for maintenance activities organization. Preventive maintenance activities are usually planned in advance: production is stopped and all maintenance activities... more
In this paper, we propose a multi-skill project scheduling problem model for maintenance activities organization. Preventive maintenance activities are usually planned in advance: production is stopped and all maintenance activities should be processed as fast as possible in order to restart production. Moreover, these human resource handled activities require specific skills and are subject to precedence constraints. The main difference with Multi-Skill Project Scheduling Problem is that some activities may be submitted to disjunctive constraints due to material constraints of the production channel that we consider. We describe how we use these constraints to improve usual MSPSP resolution methods. This study, based on a real industrial case found in MDGBB1 SKF factories, deals with the prac- tical organization of Total Productive Maintenance activities. Total Productive Maintenance (also known as TPM (7)) is a maintenance concept that includes scheduled maintenance downtime of pr...
Managing more than one project is a challenging decision-making process, and the problem that is already included in the NP-Hard class becomes more difficult when the multi-mode nature of activities are added. In this study, we propose a... more
Managing more than one project is a challenging decision-making process, and the problem that is already included in the NP-Hard class becomes more difficult when the multi-mode nature of activities are added. In this study, we propose a model for the multi-mode resourceconstrained multi-project scheduling problem with three projects each with four activities in order to schedule kitchen projects produced in a small job-shop. In the proposed model, it is assumed that each activity has two modes. There are two different types of resource in each mode. There is a cost to change between modes, and earliness and tardiness costs can occur as project due dates are assumed to be known in advance. The mathematical model of the problem is presented in the study. In the model, the objective is to minimize the sum of the cost of mode changing with earliness and tardiness costs. The proposed model is solved by GAMS optimization program by considering different scenarios for the scheduling problem and the obtained results are found promising.
