An interactive computerized algorithm for multicriteria vehicle routing problems
Computers and Industrial Engineering
Memetic algorithms: a short introduction
New ideas in optimization
An updated survey of GA-based multiobjective optimization techniques
ACM Computing Surveys (CSUR)
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
A cutting plane algorithm for the capacitated arc routing problem
Computers and Operations Research
A Tabu Search Heuristic for the Capacitated Arc Routing Problem
Operations Research
A Hierarchical Relaxations Lower Bound for the Capacitated Arc Routing Problem
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 3 - Volume 3
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A genetic algorithm for a bi-objective capacitated arc routing problem
Computers and Operations Research
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Development and assessment of the SHARP and RandSHARP algorithms for the arc routing problem
AI Communications - 18th RCRA International Workshop on “Experimental evaluation of algorithms for solving problems with combinatorial explosion”
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The Capacitated Arc Routing Problem (CARP) is a very hard vehicle routing problem raised for instance by urban waste collection. In addition to the total route length (the only criterion minimized in the academic problem), waste management companies seek to minimize also the length of the longest trip. In this paper, a bi-objective genetic algorithm is presented for this more realistic CARP, never studied before in literature. Based on the NSGA-II template, it includes two-key features: use of good constructive heuristics to seed the initial population and hybridization with a powerful local search procedure. This genetic algorithm is appraised on 23 classical CARP instances, with excellent results. For instance, for a majority of instances, its efficient solutions include an optimal solution to the academic CARP (minimization of the total route length).