Volume 44 | Number 2 | Year 2017 | Article Id. IJMTT-V44P520 | DOI : https://doi.org/10.14445/22315373/IJMTT-V44P520
Objectives: Using the multi-objective method is to solve the partial flexible open-shop scheduling problem (PFOSP), this paper optimizes the three objectives of minimizing the makespan, the maximum workload and the total workload of machine, Methods and Statistical Analysis: analyzes the relations between the three optimization objectives in detail, and decides to Findings: minimize the makespan and the maximum workload during the process route selection and to minimize the total workload of machine processing time during the process scheduling. According to the characteristics of multi-objective optimization, the author redesigns the update mode and state transition probabilistic formula for local meta-heuristic information of ant in the optimized ant colony algorithm. Application /Improvements: The simulation experiment proves the based effectiveness of the mixed optimization algorithm of ant colony algorithm and particle swarm algorithm.
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N. Jananeeswari, Dr.S.Jayakumar, Dr.M.Nagamani, "Multi-Objective for a Partial Flexible Open Shop Scheduling Problem using Hybrid Based Particle Swarm Algorithm and Ant Colony Optimization," International Journal of Mathematics Trends and Technology (IJMTT), vol. 44, no. 2, pp. 100-107, 2017. Crossref, https://doi.org/10.14445/22315373/IJMTT-V44P520