Project Scheduling in Decision-Theoretic Competitive Bidding

Accurate cost estimates for an incoming order are critical in formulating the optimal bidding strategy. When a firm is approaching its resource capacity in the short-run, adding a new job into the system may cause violations of the due date requirements, thus penalty costs arise. In this study we propose a two-stage scheduling-based optimal bidding model. Stage-I considers a resource-constrained project scheduling problem (RCPSP) minimizing the weighted tardiness (penalty costs). Due to the NP-completeness of the Stage-I model, we propose a tabu search metaheuristic to obtain a high quality solution with reasonable computational time. The obtained cost estimates are then fed into the Stage-II decision-theoretic competitive bidding model to find the optimal bidding price. Advantages and extensions of the proposed model are discussed.