Mostafa Zaree; Reza Kamranrad; Mojtaba Zaree; Iman Emami
Abstract
Today's competitive conditions have caused the projects to be carried out in the least possible time with limited resources. Therefore, managing and scheduling a project is a necessity for the project. The timing of a project is to specify a sequence of times for a series of related activities. According ...
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Today's competitive conditions have caused the projects to be carried out in the least possible time with limited resources. Therefore, managing and scheduling a project is a necessity for the project. The timing of a project is to specify a sequence of times for a series of related activities. According to their priority and their latency, so that between the time the project is completed and the total cost is balanced. Given the balance between time and cost, and to achieve these goals, there are several options that should be considered among existing options and ultimately the best option to perform activities to complete the project. In this research, a mathematical model of project scheduling with multiple goals based on cost patterns and consideration of resource constraints is presented, and this problem is considered as a problem for NP-hard issues in family hybrid optimization. GA، PSO and SA Meta-heuristic algorithms are used to solve the proposed model in project scheduling and the results are compared with each other.
Amir Hossein Hosseinian; Vahid Bardaran
Abstract
In this research, we study the multi-skill resource-constrained project scheduling problem, where there are generalized precedence relations between project activities. Workforces are able to perform one or several skills, and their efficiency improves by repeating their skills. For this problem, a mathematical ...
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In this research, we study the multi-skill resource-constrained project scheduling problem, where there are generalized precedence relations between project activities. Workforces are able to perform one or several skills, and their efficiency improves by repeating their skills. For this problem, a mathematical formulation has been proposed that aims to optimize project completion time, reworking risks of activities, and costs of processing the activities, simultaneously. A modified version of the Pareto Archived Evolution Strategy (MV-PAES) is developed to solve the problem. Contrary to the basic PAES, this algorithm operates based on a population of solutions. For the proposed method, we devised crossover and mutation operators, which strengthen this algorithm in exploring solution space. Comprehensive numerical tests have been conducted to evaluate the performance of the MV-PAES in comparison with two other meta-heuristics. The outputs show the excellence of the MV-PAES in comparison with other methods. A real-world software development project has been studied to demonstrate the practicality of the proposed model for real-world environment. The influence of competency evolution has been investigated in this case study. The results imply that the competency evolution has a considerable impact on the objective function values.