Reactive Tabu Search for Job-shop scheduling problems considering peak shift of electric power energy consumption

2016 ◽  
Author(s):  
Shuhei Kawaguchi ◽  
Yoshikazu Fukuyama
Keyword(s):  
Energy Consumption ◽  
Tabu Search ◽  
Electric Power ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Peak Shift ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Reactive Tabu Search

Entropy-Enhanced Genetic Algorithm with Tabu Search for Job Shop Scheduling Problems

2012 ◽  
Vol 590 ◽  
pp. 557-562 ◽  
Author(s):  
Ying Jie Huang ◽  
Xi Fan Yao ◽  
Dong Yuan Ge ◽  
Yong Xiang Li
Keyword(s):  
Genetic Algorithm ◽  
Tabu Search ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Search Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Traditional Scheduling ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Benchmark Instances

By combining Genetic algorithm with Tabu search algorithm and adjusting crossover rate and mutation rate based on information entropy, a hybrid genetic algorithm was proposed for larger-scale job shop scheduling problems, and the benchmark instances were used to verify the algorithm with simulation. Simulation results show that the proposed algorithm can solve larger-scale job shop scheduling problems, and it has obvious advantages over traditional scheduling algorithms.

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