Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
SSPMO: A Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization
INFORMS Journal on Computing
An effective memetic algorithm for the cumulative capacitated vehicle routing problem
Computers and Operations Research
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This work is motivated by a real problem posed to the authors by a company in Tenerife, Spain. Given a set of service orders,daily routes have to be designed in order to minimize the total traveled distance while balancing the workload of drivers in terms of required time. A bi-objective mixed-integer linear model for the problem is formulated and a solution approach, based on metaheuristics, is proposed. One the main handicaps associated to this approach is the fact that it is very time consuming for non-standard literature instances, mainly due to the the initial solution generation method. Therefore, the goal of this work is to study the performance of three different ways to build the initial solutions and observe what is their impact on the approximations of the Pareto Front for Solomon instances of 100 customers. Results obtained on a real instance are also discussed.