Solving a sealed-bid reverse auction problem by multiple-criterion decision-making methods

AbstractThis study presents a model for solving the sealed-bid, multiple-issue reverse auction problem, using multiple-criterion decision-making approaches, such that the interests of both the buyer and the supplier are satisfied. On the supplier side, the bid construction process is formulated as a fuzzy multiple-objective programming problem, and is solved using an exhausted enumeration algorithm which adjusts the production plan in accordance with the buyer’s demand, based on the current master production schedule (MPS) and the available-to-promise (ATP) inventory. The use of the information of MPS and ATP enables the supplier to make accurate estimates of the production costs associated with specific delivery dates, and thus facilitates the construction of a bid which is both profitable and likely to secure the contract. On the buyer side, the winner determination process is treated as a multiple-attribute decision-making problem, and is solved using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The validity of the proposed approach is demonstrated via an illustrative example

Customer order fulfillment based on a rolling horizon available-to-promise mechanism: solution by fuzzy approach and genetic algorithm

[[abstract]]This study attempts to solve a dynamic order promising problem, where customer requests arrive in a random fashion, and the producer processes customer orders on a batch basis. This decision process repeated for every predefined batching interval, and the current decision-making must take into account the previously committed orders. The problem is formulated as a mixed integer programming model with fuzzy constraints, which express the decision-maker’s subjective judgment regarding customer’s price tolerance. The proposed model embeds the advanced available-to-promise (AATP) concept to support accurate computation of profit and customer order promising. A genetic algorithm is developed to solve the problem. Experiments by computer simulations are carried out to demonstrate the proposed approach.[[notice]]補正完

Solving a sealed-bid reverse auction problem by multiple-criterion decision-making methods

[[abstract]]This study presents a model for solving the sealed-bid, multiple-issue reverse auction problem, using multiple-criterion decision-making approaches, such that the interests of both the buyer and the supplier are satisfied. On the supplier side, the bid construction process is formulated as a fuzzy multiple-objective programming problem, and is solved using an exhausted enumeration algorithm which adjusts the production plan in accordance with the buyer’s demand, based on the current master production schedule (MPS) and the available-to-promise (ATP) inventory. The use of the information of MPS and ATP enables the supplier to make accurate estimates of the production costs associated with specific delivery dates, and thus facilitates the construction of a bid which is both profitable and likely to secure the contract. On the buyer side, the winner determination process is treated as a multiple-attribute decision-making problem, and is solved using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The validity of the proposed approach is demonstrated via an illustrative example.[[incitationindex]]SCI[[countrycodes]]GB