A re-entrant hybrid flow shop scheduling problem with machine eligibility constraints

• Published in: International journal of production research Vol. 56; no. 16; pp. 5293 - 5305
• Main Authors: Zhang, Xiang Yi, Chen, Lu
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 18.08.2018; Taylor & Francis LLC
• Subjects: Algorithms; Constraints; Crossovers; differential evolution; Evolutionary algorithms; hybrid flow shop; Integer programming; Job shop scheduling; Job shops; Linear programming; machine eligibility; Mixed integer; Production scheduling; rotor production; scheduling; Sensitivity analysis; Tightness
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2017.1408971

A production scheduling problem originating from a real rotor workshop is addressed in the paper. Given its specific characteristics, the problem is formulated as a re-entrant hybrid flow shop scheduling problem with machine eligibility constraints. A mixed integer linear programming model of the problem is provided and solved by the Cplex solver. In order to solve larger sized problems, a discrete differential evolution (DDE) algorithm with a modified crossover operator is proposed. More importantly, a new decoder addressing the machine eligibility constraints is developed and embedded to the algorithm. To validate the performance of the proposed DDE algorithm, various test problems are examined. The efficiency of the proposed algorithm is compared with two other algorithms modified from the existing ones in the literatures. A one-way ANOVA analysis and a sensitivity analysis are applied to intensify the superiority of the new decoder. Tightness of due dates and different levels of scarcity of machines subject to machine eligibility restrictions are discussed in the sensitivity analysis. The results indicate the pre-eminence of the new decoder and the proposed DDE algorithm.