Textile Flexible Job-Shop Scheduling Based on a Modified Ant Colony Optimization Algorithm
Source abstract
Abstract
To improve the workshop production efficiency of textile enterprises and balance the total operating time of all machines in each operation, this paper proposes a modified algorithm based on the combination of the ant colony optimization (ACO) algorithm and production products, which we call the product ant colony optimization (PACO) algorithm. The local pheromone update rule in the ACO algorithm is modified through the close relationship between textile machinery and production products in the textile workshop; the pheromone is then introduced into production products based on the constraints of the textile machine. A heuristic function is designed to improve the utilization rate of textile machines to increase the heuristic value of machines that are less frequently used in the algorithm iteration process. In addition, this paper combines the convergence speed and the global search ability of the algorithm with a designed variable pheromone evaporate parameter. The comparison among the initially designed PACO algorithm, the separately modified PACO algorithm, and the integratively modified PACO algorithm demonstrates that the proposed enhancement effectively addresses scheduling issues in textile flexible workshops and various workshops with similar constraint conditions.
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Research context
OpenAlex topics: Scheduling and Optimization Algorithms · Assembly Line Balancing Optimization · Advanced Manufacturing and Logistics Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Information Science and Engineering, Harbin Institute of Technology at WeiHai, Weihai 264209, China
School of Ocean Engineering, Harbin Institute of Technology at Weihai, Weihai 264209, China
Funding
National Key R&D Program of China · Taishan Scholars · Ministry of Education industry-university cooperative education project · major scientific and technological innovation projects in Shandong Province
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