Journal
COMPUTERS & INDUSTRIAL ENGINEERING
Volume 85, Issue -, Pages 206-215Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2015.03.022
Keywords
Parallel machine scheduling; Fuzzy environment; Job deterioration; Learning effect; Multi-objective branch and bound
Ask authors/readers for more resources
The current paper investigates a non-identical parallel machine multi-objective scheduling problem in which both the deterioration and learning effects have been considered. Due to uncertainty of the parameters in real-world systems, processing times and due dates of jobs are represented here with triangular fuzzy numbers. Using the credibility measure, a nonlinear mathematical model is provided based on fuzzy chance-constrained programming (FCCP) with the aim to minimize two objective functions, namely total earliness/tardiness (ET) and maximum completion time of jobs (makespan). Since it is a mixed integer nonlinear mathematical model, there is no guarantee that the solution will obtain a global optimum. Therefore, a multi-objective branch and bound algorithm is provided by introducing an effective lower bound in order to obtain a Pareto optimal front. Computational results show that the algorithm proposed is especially useful to solve large-scale problems. (C) 2015 Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available