Bidding Decision in Reverse Auction Solved by Fuzzy Mathematical Programming and Genetic Algorithm

AbstractThis study proposes a mixed-integer programming with fuzzy constraints for solving the bidding problem in a reverse auction environment. Suppliers’ optimum bid price is determined through the compromise between profitability of the bid and possibility to win the contract. The proposed model embeds the advanced available-to-promise (AATP) concept in order to support accurate computation of profit and customer order promising. Moreover, the feasible bid price is constrained by a fuzzy upper bound to model the decision-maker's subjective judgment. A genetic algorithm is formulated to solve the problem. Performance of the proposed approach is evaluated through computer simulated experiments.