The shifting bottleneck procedure for job shop scheduling
Management Science
Sequencing in an assembly line with blocking to minimize cycle time
Operations Research
Scheduling computer and manufacturing processes
Scheduling computer and manufacturing processes
Tabu search for a class of single-machine scheduling problems
Computers and Operations Research
Operations Research: An Introduction (8th Edition)
Operations Research: An Introduction (8th Edition)
Principles of Sequencing and Scheduling
Principles of Sequencing and Scheduling
Applying adaptive algorithms to epistatic domains
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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This article presents a novel Genetic Algorithm with a greedy local search operator that may solve a wide range of sequencing and scheduling discrete optimization problems efficiently. To analyze its performance, we have tested the algorithm on the Permutation Flow-shop Scheduling Problem (PFSSP). Here we present a novel crossover scheme coupled with an innovative mutation scheme that implements local search to facilitate rapid convergence. This novel GA variant provides better results compared to other heuristics, which is apparent from the experimental results and comparisons with other existing algorithms.