A general space-time model for combinatorial optimization problems (and not only)

TL;DR

This paper introduces a comprehensive space-time model for complex combinatorial optimization problems involving facility location, timing, multiple criteria, uncertainty, and stakeholder preferences, integrating various methodologies.

Contribution

It presents a novel general space-time model combining multiple operations research problems with flexible decision-making methodologies.

Findings

Model effectively handles complex, multi-criteria, and uncertain decision problems.

Incorporates multiple methodologies like multiattribute value theory and multiobjective optimization.

Demonstrates applicability through a simple illustrative example.

Abstract

We consider the problem of defining a strategy consisting of a set of facilities taking into account also the location where they have to be assigned and the time in which they have to be activated. The facilities are evaluated with respect to a set of criteria. The plan has to be devised respecting some constraints related to different aspects of the problem such as precedence restrictions due to the nature of the facilities. Among the constraints, there are some related to the available budget. We consider also the uncertainty related to the performances of the facilities with respect to considered criteria, and plurality of stakeholders participating to the decision. The considered problem can be seen as the combination of some prototypical operations research problems: knapsack problem, location problem and project scheduling. Indeed, the basic brick of our model is a variable $x_{ilt}$ which takes value 1 if facility $i$ is activated in location $l$ at time $t$, and $0$ otherwise. Due to the conjoint consideration of a location and a time in the decision variables, what we propose can be seen as a general space-time model for operations research problems. We discuss how such a model permits to handle complex problems using several methodologies including multiple attribute value theory and multiobjective optimization. With respect to the latter point, without any loss of the generality, we consider the compromise programming and an interactive methodology based on the Dominance-based Rough Set Approach. We illustrate the application of our model with a simple didactic example.