HYBRID PARTICLE SWARM ALGORITHM FOR SCHEDULING IN CELLULAR MANUFACTURING SYSTEM- A CASE STUDY
Qazi Salman Khalid1, Muhammad Abas1, Mudassar Rauf2, Mirza Jahanzaib2, Shahid Maqsood1
ABSTRACT
Cellular Manufacturing System (CMS) lies in the heart of lean manufacturing with goal of producing the wide variety of products as efficiently 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 measures; 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.
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