Coordinating Resource Allocation during Product Transitions Using a Multifollower Bilevel Programming Model

TL;DR

This paper presents a multi-follower bilevel programming model for coordinating resource allocation during product transitions in semiconductor manufacturing, capturing hierarchical decision-making and decentralized control.

Contribution

It introduces a reformulation of the multi-follower bilevel model into a single-level problem and develops a cut-and-column generation algorithm for efficient solution.

Findings

Algorithm performs well on computational experiments.

Managerial insights on decision authority impact system performance.

Model effectively captures hierarchical resource allocation dynamics.

Abstract

We study the management of product transitions in a semiconductor manufacturing firm that requires the coordination of resource allocation decisions by multiple, autonomous Product Divisions using a multi-follower bilevel model to capture the hierarchical and decentralized nature of this decision process. Corporate management, acting as the leader, seeks to maximize the firm's total profit over a finite horizon. The followers consist of multiple Product Divisions that must share manufacturing and engineering resources to develop, produce and sell products in the market. Each Product Division needs engineering capacity to develop new products, and factory capacity to produce products for sale while also producing the prototypes and samples needed for the product development process. We model this interdependency between Product Divisions as a generalized Nash equilibrium problem at the lower level and propose a reformulation where Corporate Management acts as the leader to coordinate the resource allocation decisions. We then derive an equivalent single-level reformulation and develop a cut-and-column generation algorithm. Extensive computational experiments evaluate the performance of the algorithm and provide managerial insights on how key parameters and the distribution of decision authority affect system performance.