ORIGINAL ARTICLE Bidding-based multi-agent system for integrated process planning and scheduling: a data-mining and hybrid tabu-SA algorithm-oriented approach Sanjay Kumar Shukla & M. K. Tiwari & Young Jun Son Received: 15 December 2006 / Accepted: 7 May 2007 / Published online: 14 June 2007 # Springer-Verlag London Limited 2007 Abstract This paper conceptualizes a bidding-based multi- agent system for solving integrated process-planning and scheduling problem. The proposed architecture consists of various autonomous agents capable of communicating (bidding) with each other and making decisions based on their knowledge. Moreover, in contrast to the traditional model of integrated process-planning and scheduling problem, a new paradigm has been conceptualized by considering tool cost as a dynamic quantity rather than a constant. Tool cost is assumed to comprise tool-using cost and its repairing cost. The repairing cost is considered to depend on the tool-breaking probability, which is predicted by the data-mining agent equipped with the virtues of C- fuzzy decision tree. When a job arrives at the shop floor, the component agent announces a bid for one feature at a time to all the machine agents. Among the machine agents capable of producing the first feature, one comes forward to become a “leader”, and groups other machine agents for the processing of remaining features of the job. Once all features are assigned to the appropriate machines, the leader then sends this allocation information to the optimization agent. The optimization agent finds optimal/ near-optimal process plans and schedules via the hybrid tabu-SA algorithm. Keywords Multi-agent system . Integrated process planning and scheduling . Dynamic tool cost . C-fuzzy decision trees . Hybrid tabu-SA algorithm 1 Introduction In recent years, manufacturing enterprises have faced serious challenges and pressure from the growing tide of globalization. To survive in a competitive global market, manufacturing enterprises have to respond both promptly and effectively to the dynamic disturbances caused from internal operations or external market circumstances. More specifically, manufacturing firms must be able to produce a large variety of products efficiently and be responsive and reconfigurable to accommodate dynamic changes in prod- uct mix, product design, and demand patterns in the marketplace [11]. Agile manufacturing, a manufacturing paradigm pro- posed to deal with a dynamically changing manufacturing environment, requires artificial barriers between functioned departments and isolated islands of information [32]. One of the most important steps in this direction is to integrate process-planning and scheduling problems. Traditionally, process planning and scheduling were carried out in two distinct, sequential phases; which gives rise to the following stumbling blocks [10, 34]: – Assuming an unlimited amount of resources on the shop floor, process planners carry out the most desirable processes repeatedly. However, when the Int J Adv Manuf Technol (2008) 38:163–175 DOI 10.1007/s00170-007-1087-8 S. K. Shukla Department of Manufacturing Engineering, National Institute of Foundry and Forge Technology, Ranchi 834003, India M. K. Tiwari Department of Forge Technology, National Institute of Foundry and Forge Technology, Ranchi 834003, India Y. J. Son(*) Department of Systems and Industrial Engineering, University of Arizona, Tucson, AZ 85721-0020, USA e-mail: son@sie.arizona.edu