A Simulated Annealing Algorithm for the Generation of Multi-Factory Aggregate Production Plan P. Ashoka Varthanan 1 '*, Dr. N. Murugan 2 and Dr. G. Mohan Kumar 3 yutsrponmlkihgfedcbaTSPMLKIEDC 1 Lecturer 2 Professor 3 Principal 1 Department of Mechanical Engineering Department, Sri Krishna College of Engineering and Technology, Coimbatore-641008, India. Phone: +91 9952422176. Email: ashoka_yarthanan@yahoo. com 2 Department of Mechanical Engineering, Coimbatore Institute of Technology, Coimbatore - 641 014, India. Email: drmurugan@yahoo.com 3 Park College of Engineering and Technology, Coimbatore - 641 659, India. Email: gmohankumar68@yahoo. com ABSTRACT Aggregate production plan (APP) aims to attain the highest profit level by utilizing all the resources efficiently. Most of the industries today are generating the APP separately for each plant even though they produce the same family of products in all the plants. APP devised for the plants after allocating the demand for the corresponding plants based on gross production and distribution costs is not optimum. The industry must work towards meeting the forecasted demand by creating a medium-term plan considering all its plants simultaneously. In this paper, APP is generated using simulated annealing (SA) for a multi-factory model, where the same family of products is manufactured at different localities. Data collected from a bearing manufacturing company is fitted to the mathematical model developed in this case. The parameters of the APP, viz., period-wise workforce level, quantity to be produced in regular production, overtime hours, outsourcing, finished goods inventory status and number of products sent from each plant to the demand centers are all normalized towards the objective of cost minimization. * Corresponding Author Keywords: Aggregate Production Plan, Forecasted Demand, Simulated Annealing 1.0 INTRODUCTION Aggregate production planning (APP) is defined as the simultaneous determination of production, inventory and the workforce levels of a company on a finite time horizon /1 /. Abundant research has been carried out in the area of aggregate production planning. Since Holt, Modigliani, Muth and Simon proposed the HMMS rule in 1955, researchers have developed numerous models to solve the APP problem, each with their own pros and cons 111. Nam and Logendran /3/ surveyed the range of techniques currently available for setting aggregate plans and classified each methods in terms of their ability to produce either an exact optimal or a near - optimal solution. An offline planning and online control strategy was proposed by Wang et al. IAI for solving the APP model in the case of meeting seasonal demands for multi-product scenario. An optimal control approach to continuous-time aggregate production planning problem was presented 171 Brought to you by | University of Arizona Authenticated Download Date | 6/9/15 6:00 AM