A hybrid memetic algorithm for maximizing the weighted number of just-in-time jobs on unrelated parallel machines

Authors:
F. Jolai;M. S. Amalnick;M. Alinaghian;M. Shakhsi-Niaei;H. Omrani
Affiliations:
Department of Industrial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran;Department of Industrial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran;Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran;Department of Industrial Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran;Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Venue:
Journal of Intelligent Manufacturing
Year:
2011

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Abstract

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.