The bi-objective covering tour problem
Computers and Operations Research
A provably convergent heuristic for stochastic bicriteria integer programming
Journal of Heuristics
Transportation Science
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Two metaheuristics for multiobjective stochastic combinatorial optimization
SAGA'05 Proceedings of the Third international conference on StochasticAlgorithms: foundations and applications
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
A faster algorithm for calculating hypervolume
IEEE Transactions on Evolutionary Computation
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We consider a problem faced by international aid organizations after the occurrence of a natural disaster. A supply system with intermediate warehouses has to be established to provide affected people with relief goods. A three-objective optimization model with a medium-term economic, a short-term economic, and a humanitarian objective function is used. We apply the epsilon constraint method to determine the Pareto frontier. To solve the single-objective constrained optimization problem, we propose an exact solution method as well as a ''math-heuristic'' technique building on a MILP formulation with a heuristically generated constraint pool. As a subproblem, the multiple-depot, multiple-trip capacitated team orienteering problem is solved. We present a MIP formulation and a VNS procedure for this problem. Synthetically generated instances and a real-world illustration case are used for our computational studies. The results of the math-heuristic technique are compared to those obtained from an application of the NSGA-II metaheuristic and, where possible, to those of the exact solution approach.