On the Generation of Alternative Solutions for a Perishable Food Distribution Problem

Abstract

Solving a perishable food distribution problem in a real world setting is a very complex task. This is due to products characteristics, and the requirements of customers. To ensure a safe, quality product with a desired service level, a bunch of specifications should be included during the decision/optimization process. Generally, it’s difficult to include all the parameters in the mathematical model. Thus, it’s desired to have a set of alternative solutions to select from, that allows the decision maker to consider different perspectives. For this purpose, the current work outlines the application of a Modeling to Generate Alternatives approach, that can generate a set of near optimal solutions, but maximally different from the best one. A General Variable Neighborhood Search GVNS algorithm is applied to solve the problem. We show through computational experiments how the proposed procedure allows to generate a number of diverse solutions in a single run. We also show how the consideration of a fuzzy threshold constraint may allow to obtain interesting solutions over a set of criteria calculated after the optimization process, for an a posteriori analysis.