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HYBRID PARTICLE SWARM ALGORITHM FOR SCHEDULING IN CELLULAR MANUFACTURING SYSTEM- A CASE STUDY

Author(s)
Qazi Salman Khalid Department of Industrial Engineering, UET Peshawar, Pakistan
Muhammad Abas Department of Industrial Engineering, UET Peshawar, Pakistan
Mudassar Rauf Department of Industrial Engineering, UET Taxila, Pakistan
Mirza Jahanzaib Department of Industrial Engineering, UET Taxila, Pakistan
Shahid Maqsood Department of Industrial Engineering, UET Peshawar, Pakistan
Abstract
Cellular Manufacturing System (CMS) lies in the heart of lean manufacturing with goal of producing the wide variety of products as eficiently as possible. Increase in customer demand for more customized products had forced industries to shift to CMS. Once CMS has been established scheduling becomes one of the challenging task. So, in present work, a real case study based on scheduling problem in CMS is presented and a hybrid particle swarm optimization (PSO) algorithm is proposed to achieve an optimize sequence. The PSO is integrated with NEH algorithm to achieve an optimal sequence faster. A mathematical model is presented to evaluate two conflicting performance mea sures; minimization of work in process (WIP) and maximization of average machine cell utilization. Implementation of proposed algorithm had increased the utilization from 65% to 82 % while minimized the WIP to 6 parts from 25parts.
Publication Details
Page(s) 85-92
DOI DOI not available
Published Journal: Journal of Engineering and Applied Sciences, Volume: 38, Issue: 1, Year: 2019

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Keywords
Particle Swarm Optimization, Machine utilization, Work in Process, Cellular Manufacturing, Hybrid algorithm
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