FMS scheduling with knowledge based genetic algorithm approach A. Prakash a , Felix T.S. Chan b,⇑ , S.G. Deshmukh a a Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India b Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong article info Keywords: Scheduling Flexible manufacturing system Genetic algorithm Knowledge management KBGA abstract In this paper a complex scheduling problem in flexible manufacturing system (FMS) has been addressed with a novel approach called knowledge based genetic algorithm (KBGA). The literature review indicates that meta-heuristics may be used for combinatorial decision-making problem in FMS and simple genetic algorithm (SGA) is one of the meta-heuristics that has attracted many researchers. This novel approach combines KB (which uses the power of tacit and implicit expert knowledge) and inherent quality of SGA for searching the optima simultaneously. In this novel approach, the knowledge has been used on four different stages of SGA: initialization, selection, crossover, and mutation. Two objective functions known as throughput and mean flow time, have been taken to measure the performance of the FMS. The useful- ness of the algorithm has been measured on the basis of number of generations used for achieving better results than SGA. To show the efficacy of the proposed algorithm, a numerical example of scheduling data set has been tested. The KBGA was also tested on 10 different moderate size of data set to show its robust- ness for large sized problems involving flexibility (that offers multiple options) in FMS. Ó 2010 Elsevier Ltd. All rights reserved. 1. Introduction Owing to the globalization of the market, increasing demands of the customized products and rapidly changing needs of customers, the manufacturers are finding it difficult to survive under the forces of increased competition and increased customers’ expecta- tions. Therefore, to sustain in the global market, their focus is to develop a manufacturing system that can fulfil all the demanded requirements within due dates at a reasonable cost. Among all the existing manufacturing system, they require a manufacturing system having the flexibility to make the customized product with medium volume. Therefore, they are motivated to consider flexible manufacturing system (FMS), which is a compromise between job shop manufacturing system and batch manufacturing system. Flexible manufacturing system is a system, which is equipped with the several computer-controlled machines, having the facility of automatic changing of tools and parts. The machines are intercon- nected by automatic guided vehicles (AGVs), pallets and several storage buffers. These components are connected and governed by computer using the local area network (LAN). The exquisiteness of this system is that it gleaned the ideas both from the flow shop and batch shop manufacturing system. The prominent literature has several descriptions of FMS and its inherent feature of flexibil- ity has been addressed by many researchers, e.g. Upton (1994), Wadhwa and Browne (1989), Wadhwa, Rao, and Chan (2005), etc. Wadhwa and Rao (2000) have defined the flexibility as the ability to deal with change by judiciously providing and exploiting controllable options dynamically. Due to this flexibility, some deci- sion-making problems have occurred in the system. In order to run the system efficiently, the decision points and their importance should be defined and assessed very carefully (Wadhwa & Bhag- wat, 1998; Wadhwa & Browne, 1989; Caprihan & Wadhwa, 1997, etc.). According to Stecke (1983) and Gen, Lin, and Zhang (2009), there are four stages of decision problems for the FMS: designing, planning, scheduling, and control. The center of attention of authors is on the scheduling problem after considering that design- ing and planning phase has been over. In the field of manufacturing control problems of an FMS, scheduling is an extensive area for re- search which is still alluring many a researchers. Scheduling of operations is one of the most critical issues in the planning and managing of manufacturing processes. Scheduling problem is an assignment problem, which can be defined as the assigning of available resources (machines) to the activities (oper- ations) in such a manner that maximizes the profitability, flexibil- ity, productivity, and performance of a production system. This problem will increase with the augmentation of rapid changing of the product mix ratio, which is defined as the proportion of each job in each production lot. To find the best schedule can be very easy or very difficult, depending on the shop environment, the pro- cess constraints, and the performance indicator (Pinedo, 2002). The 0957-4174/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2010.09.002 ⇑ Corresponding author. E-mail addresses: anujpra@gmail.con (A. Prakash), mffchan@inet.polyu.edu.hk (F.T.S. Chan), deshmukh@mech.iitd.ernet.in (S.G. Deshmukh). Expert Systems with Applications 38 (2011) 3161–3171 Contents lists available at ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa