DocumentCode :
2478295
Title :
PSO algorithm for hot-milling batch planning problem
Author :
Zhang, Tao ; Wang, Lei ; Chu, Xiaoxuan ; Zhang, Yuejie
Author_Institution :
Sch. of Inf. Manage. & Eng., Shanghai Univ. of Finance & Econ., Shanghai
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
1072
Lastpage :
1076
Abstract :
In this paper, the hot strip mill batch planning problem is summed as a Prize Collecting Vehicle Routing Problem (PCVRP). According to the hot-milling technical rules, the inverse bounce of the width and the thickness of the steel strips are considered, the inverse bounce penalty table is designed and an improved multi-objective mathematics programming model is presented. To solve this problem, the improved Particle Swarm Optimization (PSO) is used. With the best parameters, computational results show that the best solution obtained by the algorithm, the probability of the average load and the effort of time are all satisfying.
Keywords :
batch processing (industrial); mathematical programming; milling; particle swarm optimisation; production planning; steel; strips; travelling salesman problems; average load probability; hot-milling batch planning problem; inverse bounce penalty table; multiobjective mathematics programming model; particle swarm optimization algorithm; prize collecting vehicle routing problem; steel strip thickness; steel strip width; Ant colony optimization; Capacity planning; Mathematical model; Milling; Production planning; Routing; Slabs; Steel; Strips; Vehicles; Hot-milling Batch Planning; Particle Swarm Optimization; Prize Collecting Vehicle Routing Problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
Type :
conf
DOI :
10.1109/WCICA.2008.4593070
Filename :
4593070
Link To Document :
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