arXiv subjects

Reha Uzsoy

Publications and source records attributed to Reha Uzsoy.

3 recordsLinked to original sources

arXiv2026

Release Date Optimization in MRP Using Clearing Functions

This paper integrates a clearing function (CF)-based release planning approach into Material Requirements Planning (MRP) to address its limitations in modeling capacity constraints and dynamic lead times. The proposed optimization model replaces MRP's backward scheduling step while preserving its overall structure. Performance is evaluated through simulation experiments on two flow shop systems that explore a range of demand uncertainties and utilization levels. Computational results show that the proposed approach is capable of yielding significant improvements over the conventional backward scheduling approach, due to its ability to compute planned lead times for individual production orders as opposed to BOM items.

eess.SY↗

arXiv2024

All You Need is an Improving Column: Enhancing Column Generation for Parallel Machine Scheduling via Transformers

We present a neural network-enhanced column generation (CG) approach for a parallel machine scheduling problem. The proposed approach utilizes an encoder-decoder attention model, namely the transformer and pointer architectures, to develop job sequences with negative reduced cost and thus generate columns to add to the master problem. By training the neural network offline and using it in inference mode to predict negative reduced costs columns, we achieve significant computational time savings compared to dynamic programming (DP). Since the exact DP procedure is used to verify that no further columns with negative reduced cost can be identified at termination, the optimality guarantee of the original CG procedure is preserved. For small to medium-sized instances, our approach achieves an average 45% reduction in computation time compared to solving the subproblems with DP. Furthermore, the model generalizes not only to unseen, larger problem instances from the same probability distribution but also to instances from different probability distributions than those presented at training time. For large-sized instances, the proposed approach achieves an 80% improvement in the objective value in under 500 seconds, demonstrating both its scalability and efficiency.

cs.LG↗

arXiv2024

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

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.

econ.TH↗