A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem

The unrelated parallel machine scheduling problem aims to assign jobs independent machines with sequence-dependent setup times so that the makespan is minimized. When many practical considerations are introduced, solving resulting challenging, especially when problems of realistic sizes interest. In this study, in addition conventional objective minimizing makespan, we further consider burn-in (B/I) procedure required practice; need ensure results satisfy B/I ratio constrained by equipment. To solve complicated problem, propose a population-based simulated annealing algorithm embedded variable neighborhood descent technique. Empirical show proposed solution strategy outperforms commonly used commercial optimization package; it can obtain schedules better than practice, and does more efficient manner.