Hybrid genetic algorithm for bi-objective resource-constrained project scheduling

Küçüksayacıgil, Fikri and Ulusoy, Gündüz (2020) Hybrid genetic algorithm for bi-objective resource-constrained project scheduling. Frontiers of Engineering Management, 7 (3). pp. 426-446. ISSN 2095-7513 (Print) 2096-0255 (Online)

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In this study, we considered a bi-objective, multi-project, multi-mode resource-constrained project scheduling problem. We adopted three objective pairs as combinations of the net present value (NPV) as a financial performance measure with one of the time-based performance measures, namely, makespan (Cmax), mean completion time (MCT), and mean flow time (MFT) (i.e., minCmax/maxNPV, minMCT/maxNPV, and minMFT/maxNPV). We developed a hybrid non-dominated sorting genetic algorithm II (hybrid-NSGA-II) as a solution method by introducing a backward–forward pass (BFP) procedure and an injection procedure into NSGA-II. The BFP was proposed for new population generation and post-processing. Then, an injection procedure was introduced to increase diversity. The BFP and injection procedures led to improved objective functional values. The injection procedure generated a significantly high number of non-dominated solutions, thereby resulting in great diversity. An extensive computational study was performed. Results showed that hybrid-NSGA-II surpassed NSGA-II in terms of the performance metrics hypervolume, maximum spread, and the number of non-dominated solutions. Solutions were obtained for the objective pairs using hybrid-NSGA-II and three different test problem sets with specific properties. Further analysis was performed by employing cash balance, which was another financial performance measure of practical importance. Several managerial insights and extensions for further research were presented.
Item Type: Article
Uncontrolled Keywords: Backward–forward scheduling, hybrid bi-objective genetic algorithm, injection procedure, maximum cash balance, multi-objective multi-project multi-mode resource-constrained project scheduling problem
Subjects: T Technology > T Technology (General) > T055.4-60.8 Industrial engineering. Management engineering
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering
Faculty of Engineering and Natural Sciences
Depositing User: Gündüz Ulusoy
Date Deposited: 15 Apr 2021 18:46
Last Modified: 15 Apr 2021 18:46
URI: https://research.sabanciuniv.edu/id/eprint/41405

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