Robust optimization approach for short‐term scheduling of batch plants under demand uncertainty?

Abstract

Purpose

The purpose of this paper is to propose a robust optimization approach for the short‐term scheduling of batch plants under demand uncertainty where the uncertain parameters can be described by a normal distribution function.

Design/methodology/approach

The robust optimization formulation introduces a small number of auxiliary variables and additional constraints into the original mixed integer linear programming problem, generating a deterministic robust counterpart problem which provides the optimal solution given the magnitude of the uncertain data, a feasibility tolerance, and a reliability level.

Findings

Developed robust optimization approaches produce robust solutions for uncertainties in both the coefficients and right‐hand‐side parameters of the linear inequality constraints and can be applied to address the problem of production scheduling with uncertain parameters.

Research limitations/implications

The choice of the magnitude of the uncertain data, a feasibility tolerance, and a reliability level are the main limitation of the model.

Practical implications

Very useful advice for short‐term scheduling of batch plants under demand uncertainty.

Originality/value

The paper proposes a robust optimization approach for short‐term scheduling of batch plants under demand uncertainty. Computational results are presented to demonstrate the effectiveness of the proposed approach.

Citation

Zhu, J., Gu, X. and Gu, W. (2011), "Robust optimization approach for short‐term scheduling of batch plants under demand uncertainty?", Kybernetes, Vol. 40 No. 5/6, pp. 860-870. https://doi.org/10.1108/03684921111142412