A framework for the interactive resolution of multi-objective vehicle routing problems

TL;DR

This paper introduces an interactive framework for solving complex multi-objective vehicle routing problems, incorporating local search, flexible constraints, and decision-maker preferences, demonstrated through prototype implementation and initial testing.

Contribution

It presents a novel flexible framework combining local search and interactive decision support for complex vehicle routing problems with multiple constraints and objectives.

Findings

Successful prototype implementation demonstrated feasibility.

Initial test runs on multi-depot problems with time windows.

Framework effectively incorporates decision-maker preferences.

Abstract

The article presents a framework for the resolution of rich vehicle routing problems which are difficult to address with standard optimization techniques. We use local search on the basis on variable neighborhood search for the construction of the solutions, but embed the techniques in a flexible framework that allows the consideration of complex side constraints of the problem such as time windows, multiple depots, heterogeneous fleets, and, in particular, multiple optimization criteria. In order to identify a compromise alternative that meets the requirements of the decision maker, an interactive procedure is integrated in the resolution of the problem, allowing the modification of the preference information articulated by the decision maker. The framework is prototypically implemented in a computer system. First results of test runs on multiple depot vehicle routing problems with time windows are reported.