An Enhanced Differential Evolution Algorithm with Fast Evaluating Strategies for TWT-NFSP with SSTs and RTs

Abstract

The no-wait flow-shop scheduling problem with sequence-dependent setup times and release times (i.e., the NFSP with SSTs and RTs) is a typical NP-hard problem. This paper proposes an enhanced differential evolution algorithm with several fast evaluating strategies, namely, DE_FES, to minimize the total weighted tardiness objective (TWT) for the NFSP with SSTs and RTs. In the proposed DE_FES, the DE-based search is adopted to perform global search for obtaining the promising regions or solutions in solution space, and a fast local search combined with three presented strategies is designed to execute exploitation from these obtained regions. Test results and comparisons with two effective meta-heuristics show the effectiveness and robustness of DE_FES.

A Hybrid Bat Algorithm for Solving the Three-Stage Distributed Assembly Permutation Flowshop Scheduling Problem

“…More and more scholars are focusing more on the improvement of algorithmic aspects. For the no-wait flow shop scheduling problem that depends on time series, Hu et al [18] proposed an enhanced differential evolutionary algorithm. Subsequently, Seidgar [19] took minimizing the weighted sum of expected completion time and average completion time as the solution objective and proposed four metaheuristic algorithms; namely, genetic algorithm, imperialistic competition algorithm, cloud theory-based simulated annealing, and adaptive differential evolution algorithm.…”