Abstract
High transportation costs and poor quality of service are common vulnerabilities in various logistics networks, especially in food distribution. Here we propose a many-objective Customer-centric Perishable Food Distribution Problem that focuses on the cost, the quality of the product, and the service level improvement by considering not only time windows but also the customers’ target time and their priority. Recognizing the difficulty of solving such model, we propose a General Variable Neighborhood Search (GVNS) metaheuristic based approach that allows to efficiently solve a subproblem while allowing us to obtain a set of solutions. These solutions are evaluated over some non-optimized criteria and then ranked using an a posteriori approach that requires minimal information about decision maker preferences. The computational results show (a) GVNS achieved same quality solutions as an exact solver (CPLEX) in the subproblem; (b) GVNS can generate a wide number of candidate solutions, and (c) the use of the a posteriori approach makes easy to generate different decision maker profiles which in turn allows to obtain different rankings of the solutions.
Highlights
In recent years, the global food market has shown substantial growth; posing new challenges, including in the global logistics market of perishable foods
The proposed approach consists of two main steps: (1) we solve a subproblem using a General Variable Neighbourhood Search (GVNS) algorithm which generates a set of different solutions and (2) using the decision-maker preferences, those solutions are ranked using a possibility degree approach
We propose a strategy that starts by solving a sub-problem considering only the cost minimization objective, using a General Variable Neighbourhood Search algorithm (GVNS)
Summary
The global food market has shown substantial growth; posing new challenges, including in the global logistics market of perishable foods. A vehicle routing problem with time windows is extended to consider (in addition to the cost minimization), other objectives centred on the quality of service issues. It is clear that the addition of multiple conflicting objectives and many parameters in the model formulation increase its complexity up to a point where it cannot be solved: either because the model is unsolvable or a certain problem’s information is not available at the solving stage In this situation, providing a set of alternative solutions (set of routes), that can be examined from different perspectives, is highly desirable. The proposed approach consists of two main steps: (1) we solve a subproblem using a General Variable Neighbourhood Search (GVNS) algorithm which generates a set of different solutions and (2) using the decision-maker preferences, those solutions are ranked using a possibility degree approach In this way, a best compromise solution can be selected. The last section is devoted to conclusions and provide some perspectives for future research
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