A bidding decision model in multiagent supply chain planning

The multiagent environment for supply chain planning application is based on a framework unifying the internal behaviour of agents and coordination among agents. This system presents a formal view of coordination using Contract Net Protocol that relies on the basic loop of agent behaviours: order receiving, order announcement, bid calculation, and order scheduling followed by order execution. Among these, bid calculation is most difficult. It needs to determine the quantity, cost and time in which a new order can be implemented. Fuzzy programming has made progress in mathematics since Bellman and Zadeh first studied decision-making in a fuzzy mathematics programming. Currently there are many valuable works in this field and fuzzy programming has become an effective tool to deal with the decision-making problems in fuzzy systems. Similarly, stochastic programming is a useful tool to treat decision-making problems in a stochastic system. However, in many practical systems, fuzzy factors and random factors arise concurrently, and this problem has not received the attention it deserves. Therefore, there is a need to develop a new kind of optimization technique to make decisions in a fuzzy random system. In this paper, we build the Bid Calculation model, including a random parameter set, the set of product quantity that will be stored to inventory, a fuzzy parameter set, the Maximum Sales Rates set, and we discuss an approach to solve the model, as well as present an implementation procedure with the genetic algorithm method.