A faster exact method for solving the robust multi-mode resource-constrained project scheduling problem

TL;DR

This paper introduces a faster mixed-integer linear programming method for solving the robust multi-mode resource-constrained project scheduling problem under uncertainty, significantly improving computational efficiency and solution optimality.

Contribution

It proposes a new formulation that is easier to implement and outperforms existing methods in speed and problem-solving capacity.

Findings

Solution times are significantly reduced.

Over 40% more instances solved to optimality.

Method outperforms current state-of-the-art approaches.

Abstract

This paper presents a mixed-integer linear programming formulation for the multi-mode resource-constrained project scheduling problem with uncertain activity durations. We consider a two-stage robust optimisation approach and find solutions that minimise the worst-case project makespan, whilst assuming that activity durations lie in a budgeted uncertainty set. Computational experiments show that this easy-to-implement formulation is many times faster than the current state-of-the-art solution approach for this problem, whilst solving over 40% more instances to optimality over the same benchmarking set.