Design of high-performing hybrid meta-heuristics for unrelated parallel machine scheduling with machine eligibility and precedence constraints. Issue 4 (2nd April 2016)

• Record Type: Journal Article
• Authors: Afzalirad, Mojtaba; Rezaeian, Javad
• Is Part Of: Engineering optimization. Volume 48:Issue 4(2016)
• Page Start: 706
• Page End: 726
• Publication Date: 2016-04-02
• Subjects: unrelated parallel machine scheduling -- machine eligibility restrictions -- precedence constraints -- genetic algorithm -- ant colony optimization; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2015.1042475
• Languages: English
• ISSNs: 0305-215X

Abstract

Abstract : This study involves an unrelated parallel machine scheduling problem in which sequence-dependent set-up times, different release dates, machine eligibility and precedence constraints are considered to minimize total late works. A new mixed-integer programming model is presented and two efficient hybrid meta-heuristics, genetic algorithm and ant colony optimization, combined with the acceptance strategy of the simulated annealing algorithm (Metropolis acceptance rule), are proposed to solve this problem. Manifestly, the precedence constraints greatly increase the complexity of the scheduling problem to generate feasible solutions, especially in a parallel machine environment. In this research, a new corrective algorithm is proposed to obtain the feasibility in all stages of the algorithms. The performance of the proposed algorithms is evaluated in numerical examples. The results indicate that the suggested hybrid ant colony optimization statistically outperformed the proposed hybrid genetic algorithm in solving large-size test problems.