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Application of hybrid swarming algorithm on flexible job shop scheduling problems
Author(s) -
Zhang Yi,
Sun Mengdi,
Xu Yong
Publication year - 2021
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.6348
Subject(s) - ant colony optimization algorithms , swarming (honey bee) , computer science , mathematical optimization , job shop scheduling , algorithm , scheduling (production processes) , mathematics , routing (electronic design automation) , botany , biology , computer network
In this article, we present an improved hybrid algorithm based on ant colony optimization and the polycephalum algorithm. First, we use improved the probability selection mechanism in the ant colony algorithm in order to improve the efficiency of next point searching. Second, in each iteration we update the pheromone concentration of the optimal route by using the polycephalum algorithm. We regard the starting point of the optimal route as the water injection point and the end point as the water outlet point. The hybrid algorithm is compared on multiple TSPLIB problems and flexible job shop scheduling problems. And experiments show that the improved algorithm has good application results and resultful in accuracy and optimal solutions.