Simulated annealing: theory and applications
Simulated annealing: theory and applications
BPSS: a scheduling support system for the packaging industry
Operations Research
Hybrid flow shop scheduling: a survey
Computers and Industrial Engineering
Preemptive scheduling with changeovers: using column generation technique and genetic algorithm
Computers and Industrial Engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
A new heuristic for scheduling the two-stage flowshop with additional resources
Computers and Industrial Engineering
Heuristic algorithms for the two-stage hybrid flowshop problem
Operations Research Letters
Parallel-machine scheduling to minimize makespan with fuzzy processing times and learning effects
Information Sciences: an International Journal
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In this paper, a heuristic is proposed for solving the problem of scheduling in a two-stage flowshop with parallel unrelated machines and additional renewable resources at the first stage and a single machine at the second stage. Resource requirements are arbitrary integers. The availability of additional resources is limited at every moment. The objective is the minimization of makespan. The problem is NP-hard. The proposed heuristic combines column generation technique with a genetic algorithm (the heuristic algorithm HG) or a simulated annealing algorithm (the heuristic algorithm HS). The performance analysis is performed experimentally by comparing heuristic solutions to the lower bound on the optimal makespan. Results of the computational experiment show that both the heuristic algorithms yield good quality solutions using reasonable computation time and that HS outperforms HG for the most difficult problems.