Integrated order acceptance and resource decisions under uncertainty: Robust and stochastic approaches

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See all articles by Bahman Naderi

Bahman Naderi

University of Windsor - Mechanical, Automotive & Materials Engineering

Mehmet A. Begen

Ivey Business School, University of Western Ontario

Guoqing Zhang

University of Windsor

Date Written: Jan 25, 2022

Abstract

We study the order acceptance and resource planning problem which has applications in many industries such as healthcare, logistics, and manufacturing. We extend the recent literature by considering two new features: the number of resources is a decision and processing times are uncertain. We first develop mixed integer linear programming and constraint programming models for the nominal (deterministic) problem. Second, we incorporate uncertainty in the form of both stochastic and robust optimization us- ing sample average approximation, classical robust, box uncertainty, and polyhedral-interval uncertainty set techniques. Third, to solve these models, we use three decomposition techniques, branch-relax- and-check, branch-and-check, and logic-based Benders decomposition. We equip the algorithms with subproblem relaxation, pre-processing, valid inequalities, and symmetry breaking cuts. Finally, we conduct a comprehensive simulation evaluation to draw insights from both practical and algorithmic perspectives. We compare performances of algorithms with their optimality gaps. We also provide in- sights on which uncertainty approach performs well and when to use which.

Keywords: Order acceptance, mixed-integer programming, constraint programming, robust optimization, uncertainty sets, sample average approximation model, Benders decomposition.

Suggested Citation

Naderi, Bahman and Begen, Mehmet A. and Zhang, Guoqing, Integrated order acceptance and resource decisions under uncertainty: Robust and stochastic approaches (Jan 25, 2022). Available at SSRN: https://ssrn.com/abstract=

Bahman Naderi

University of Windsor - Mechanical, Automotive & Materials Engineering ( email )

OR
Canada

Mehmet A. Begen (Contact Author)

Ivey Business School, University of Western Ontario ( email )

1255 Western Road
London, Ontario N6G 0N1
Canada

HOME PAGE: http://www.ivey.uwo.ca/faculty/MBegen

Guoqing Zhang

University of Windsor ( email )

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