Convergence of an annealing algorithm
Mathematical Programming: Series A and B
The shifting bottleneck procedure for job shop scheduling
Management Science
Journal of Computational Physics
Modern heuristic techniques for combinatorial problems
Modern heuristic techniques for combinatorial problems
Improving local search heuristics for some scheduling problems—I
Discrete Applied Mathematics - Special volume: first international colloquium on graphs and optimization (GOI), 1992
Improving local search heuristics for some scheduling problems. Part II
Discrete Applied Mathematics - Special issue on models and algorithms for planning and scheduling problems
Mathematical and Computer Modelling: An International Journal
Two-machine flowshop scheduling with a secondary criterion
Computers and Operations Research
Simulated annealing heuristic for flow shop scheduling problems with unrelated parallel machines
Computers and Operations Research
Best compromise solution for a new multiobjective scheduling problem
Computers and Operations Research
A local search using solution fragments for the 2-machine bicriteria scheduling problem
Computational Optimization and Applications
Data & Knowledge Engineering
Integrating simulation and optimization to schedule a hybrid flow shop with maintenance constraints
Computers and Industrial Engineering
MROrder: flexible job ordering optimization for online mapreduce workloads
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
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This paper develops and compares different local search heuristics for the two-stage flow shop problem with makespan minimization as the primary criterion and the minimization of either the total flow time, total weighted flow time, or total weighted tardiness as the secondary criterion. We investigate several variants of simulated annealing, threshold accepting, tabu search, and multi-level search algorithms. The influence of the parameters of these heuristics and the starting solution are empirically analyzed. The proposed heuristic algorithms are empirically evaluated and found to be relatively more effective in finding better quality solutions than the existing algorithms.