MULTI-OPTIONS BIDDING STRATEGY IN DISTRIBUTED ENVIRONMENT

Abstract

When a Make-To-Order (MTO) enterprise receives a bidding invitation from a customer, he does not know the demand is price-sensitive or time-sensitive. In order to increase the possibility of winning this contingent order, the enterprise tenders his bid with two options characterized with price and delivery time. One is for time-sensitive demand, and it ensures that the products will be delivered as soon as possible. The other is for price-sensitive demand, and it ensures that the products will be produced at the lowest cost. The enterprise is comprised of several plants that jointly produce custom products and each plant's decision is made in a distributed way. Hence, the enterprise has to coordinate the production plans of these plants to generate the two options. Since Analytical Target Cascading (ATC) can solve multi-level hierarchical distributed problem and its convergence is proven, it is adopted to coordinate the plants' planning. This paper proposes a unique bidding option generating process in which an extended ATC model is utilized to produce time-sensitive and price-sensitive options by adjusting the coefficient of delivery tardiness. The numerical study in this paper demonstrates (1) the extended ATC model works effectively; (2) ATC with augmented Lagrangian relaxation (AL-ATC) is more effective in producing solutions than ATC with quadratic penalty function (QP-ATC); (3) ATC is an effective coordination tool by comparing the solutions made by ATC and All-In-One (AIO).