Research Article

Hybrid Algorithm Based on Genetic Simulated Annealing Algorithm for Complex Multiproduct Scheduling Problem with Zero-Wait Constraint

Table 1

Classification and summarizing of algorithms solving the product scheduling problem.

DevelopmentPublicationsBackgroundObjectivesAlgorithms

Enumeration methodsJohnson [1]Flow shopMakespanMP
Bansal [2]Flow shopMakespanBB
Ozolins [4]No-wait job shopMakespanDP
Xie [2528]No-wait integrated scheduling problemMakespanMP

Metaheuristic algorithmWu [5]Flexible job shopMakespanACO
Wei [6]Flow shopMakespanGA-SA
Mudjihartono [9]Job shopMakespanGA-PSO
Liu [10]Flexible job shopCarbon footprint and makespanFOA
Nouiri [13]Flexible job shopMakespanTwo-stage PSO
Wu [14]Flexible job shopMakespan and total setup timeNSGAII
Huang [15]Flexible job shopMakespanGA
Wang [18]Dynamic job shopMakespanPSO
Nagano [8]No-wait flow shopMakespanIterated greedy algorithm
Ali [11]No-wait flow shopTotal tardinessSA
Yüksel [16]No-wait permutation flow shopTotal tardiness and energy consumptionABC and NSGAII
Wu [17]No-wait permutation flow shopMakespan and energy consumptionMultiobjective VNS
Dong [19]No-wait two-stage flow shopMakespanLinear-time combinatorial algorithm
Xu [20]No-wait permutation flow shopMakespanSelf-adaptive memetic algorithm
Ying [3, 21, 30]No-wait job shopMakespanMultistart SA
Deng [22]No-wait job shopTotal flow timeIterated greedy algorithm
Shi [7]Assembly job shopMakespanGA
Lei [23]Integrated scheduling problemMakespanGA
Zhao [29]Integrated scheduling problemMakespanGA