Research Article

A DE-LS Metaheuristic Algorithm for Hybrid Flow-Shop Scheduling Problem considering Multiple Requirements of Customers

Table 1

Comparison between previous studies and this study.

ReferencesTypes of problemsObjectivesApproaches

Pan et al. [1]Lot-streaming FSPMinimize the total weighted earliness and tardiness penaltiesDiscrete artificial bee colony
Riahi and Kazemi [6]No-wait FSPMinimize the makespanA hybrid ant colony optimization and simulated annealing algorithm
Marichelvam et al. [7]FSPMinimize the makespan and total flow timeA hybrid monkey search algorithm based on subpopulation
Ruize and Stützle [31]Permutation FSPMinimize the makespanIterated greedy algorithm
Xu et al. [32]Permutation FSPMinimize the makespan and total weighted tardinessIterated local search
Lei and Zheng [11]HFSPMinimize the total tardiness, maximum tardiness, and makespanA novel neighborhood search with global exchange
Zhang et al. [12]HFSPMinimize the total flow timeEffective modified migrating birds optimization
Yu et al. [13]HFSPMinimize the total tardinessGenetic algorithm
Pan et al. [14]HFSPMinimize the makespanNine effective metaheuristics
Tasgetiren et al. [33]Blocking FSPMinimize the makespanIterated greedy algorithm
Yagmahan and Yenisey [34]FSPMinimize the makespan and total flow timeAnt colony system algorithm
Zhang and Xing [29]FSPMinimize the makespanDifferential evolution
Zhou et al. [30]HFSPMinimize the total weighted completion timeA hybrid differential evolution with an estimation of distribution algorithm
This studyHFSPMinimize the makespan and cost of delayA hybrid differential evolution and local search