Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
The vehicle routing problem
Multicriteria Optimization
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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This work is motivated by a problem proposed to the authors by a bakery company in Northern Spain. The objective is to design the daily routes over the week in order to minimize the total traveled distance. For reducing this total distance, some flexibility in the dates of delivery is introduced, which will cause a stock. Therefore, we study the problem under the bi-objective perspective, "minimizing" simultaneously the total traveled distance and the stock. A bi-objective mixed-integer linear model for the problem is formulated and two methodologies of solution are presented. The first one is based on a series of linked variable neighborhood searches and the second one is based on NSGA-II provided of specific operators. Numerical results showing the obtained estimated Pareto front in both cases are presented.