Name
Abstract | ||
|---|---|---|
We introduce and test a new approach for the bi-objective routing problem known as the traveling salesman problem with profits. This problem deals with the optimization of two conflicting objectives: the minimization of the tour length and the maximization of the collected profits. This problem has been studied in the form of a single objective problem, where either the two objectives have been combined or one of the objectives has been treated as a constraint. The purpose of our study is to find solutions to this problem using the notion of Pareto optimality, i.e. by searching for ecient solutions and constructing an ecient frontier. We have developed an ejection chain local search and combined it with a multi- objective evolutionary algorithm which is used to generate diversified starting solutions in the objective space. We apply our hybrid meta-heuristic to synthetic data sets and demonstrate its eectiveness by |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s10852-008-9080-2 | J. Math. Model. Algorithms |
Keywords | Field | DocType |
hybrid method.,multi-objective optimization,comparing our results with a procedure that employs one of the best single-objective approaches. keywords: routing problem,ejection chain,evolutionary algorithm,multi objective optimization,profitability,synthetic data,local search,traveling salesman problem | Bottleneck traveling salesman problem,Traveling purchaser problem,Mathematical optimization,Evolutionary algorithm,Multi-objective optimization,Travelling salesman problem,Artificial intelligence,Local search (optimization),2-opt,Machine learning,Mathematics,Metaheuristic | Journal |
Volume | Issue | ISSN |
7 | 2 | 1572-9214 |
Citations | PageRank | References |
25 | 0.94 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Jozefowiez | 1 | 348 | 21.58 |
| Fred Glover | 2 | 2729 | 275.46 |
| Manuel Laguna | 3 | 1452 | 131.93 |