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Parallel batch processing machines scheduling in cloud manufacturing for minimizing total service completion time
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DOI：10.1016/j.cor.2022.105899.png)
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Abstract
En 中文
This paper considers the integrated scheduling problem of production and delivery on parallel batch processingmachines with non-identical capacities in different locations in cloud manufacturing. It is assumed that the jobshave arbitrary release times, different job sizes, unequal processing times, and unique information of customerssubmitting jobs. The service completion time of a job is the sum of the production completion time and thedelivery duration. The objective of the studied problem is to minimize the total service completion time. Amixed-integer programming (MIP) model is presented to solve this problem. Since the problem is NP-hard, anefficient heuristic algorithm and an improved particle swarm optimization algorithm are proposed. The twoproposed algorithms are compared with several state-of-the-art algorithms and the commercial optimizationsolver (Gurobi) through extensive experiments, verifying the effectiveness of the proposed algorithms.
Keywords:
Batch processing machines
Cloud manufacturing
Total service completion time
Particle swarm optimization
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C
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