Customer-Value-Based Order Acceptance Policy in Make-to-Order Manufacturing

Abstract

Creation and sustenance of long-term relationships with their customers is a key success factor in make-to-order manufacturing firms. In order to achieve both maximum cumulative profit and long-term profitable customer relationships, we integrate customer value into order acceptance decision. Then we use linear programming to model the order acceptance problem, and solve it with reinforcement learning approach. The results of simulation show that the proposed policy can achieve both maximum cumulative profit and long-term profitable customer relationships. An intelligent decision policy to control the coming orders is learned by the agent.