The Experts below are selected from a list of 28401 Experts worldwide ranked by ideXlab platform
Jeanyves Potvin - One of the best experts on this subject based on the ideXlab platform.
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an exact e constraint method for bi objective combinatorial optimization problems application to the Traveling Salesman problem with profits
European Journal of Operational Research, 2009Co-Authors: Jeanfrancois Berube, Michel Gendreau, Jeanyves PotvinAbstract:Abstract This paper describes an exact ϵ -constraint method for bi-objective combinatorial optimization problems with integer objective values. This method tackles multi-objective optimization problems by solving a series of single objective subproblems, where all but one objectives are transformed into constraints. We show in this paper that the Pareto front of bi-objective problems can be efficiently generated with the ϵ -constraint method. Furthermore, we describe heuristics based on information gathered from previous subproblems that significantly speed up the method. This approach is used to find the exact Pareto front of the Traveling Salesman Problem with Profits, a variant of the Traveling Salesman Problem in which a profit or prize value is associated with each vertex. The goal here is to visit a subset of vertices while addressing two conflicting objectives: maximize the collected prize and minimize the travel costs. We report the first exact results for this problem on instances derived from classical Vehicle Routing and Traveling Salesman Problem instances with up to 150 vertices. Results on approximations of the Pareto front obtained from a variant of our exact algorithm are also reported.
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an exact epsilon constraint method for bi objective combinatorial optimization problems application to the Traveling Salesman problem with profits
European Journal of Operational Research, 2009Co-Authors: Jeanfrancois Berube, Michel Gendreau, Jeanyves PotvinAbstract:This paper describes an exact [epsilon]-constraint method for bi-objective combinatorial optimization problems with integer objective values. This method tackles multi-objective optimization problems by solving a series of single objective subproblems, where all but one objectives are transformed into constraints. We show in this paper that the Pareto front of bi-objective problems can be efficiently generated with the [epsilon]-constraint method. Furthermore, we describe heuristics based on information gathered from previous subproblems that significantly speed up the method. This approach is used to find the exact Pareto front of the Traveling Salesman Problem with Profits, a variant of the Traveling Salesman Problem in which a profit or prize value is associated with each vertex. The goal here is to visit a subset of vertices while addressing two conflicting objectives: maximize the collected prize and minimize the travel costs. We report the first exact results for this problem on instances derived from classical Vehicle Routing and Traveling Salesman Problem instances with up to 150 vertices. Results on approximations of the Pareto front obtained from a variant of our exact algorithm are also reported.
Michel Gendreau - One of the best experts on this subject based on the ideXlab platform.
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an exact e constraint method for bi objective combinatorial optimization problems application to the Traveling Salesman problem with profits
European Journal of Operational Research, 2009Co-Authors: Jeanfrancois Berube, Michel Gendreau, Jeanyves PotvinAbstract:Abstract This paper describes an exact ϵ -constraint method for bi-objective combinatorial optimization problems with integer objective values. This method tackles multi-objective optimization problems by solving a series of single objective subproblems, where all but one objectives are transformed into constraints. We show in this paper that the Pareto front of bi-objective problems can be efficiently generated with the ϵ -constraint method. Furthermore, we describe heuristics based on information gathered from previous subproblems that significantly speed up the method. This approach is used to find the exact Pareto front of the Traveling Salesman Problem with Profits, a variant of the Traveling Salesman Problem in which a profit or prize value is associated with each vertex. The goal here is to visit a subset of vertices while addressing two conflicting objectives: maximize the collected prize and minimize the travel costs. We report the first exact results for this problem on instances derived from classical Vehicle Routing and Traveling Salesman Problem instances with up to 150 vertices. Results on approximations of the Pareto front obtained from a variant of our exact algorithm are also reported.
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an exact epsilon constraint method for bi objective combinatorial optimization problems application to the Traveling Salesman problem with profits
European Journal of Operational Research, 2009Co-Authors: Jeanfrancois Berube, Michel Gendreau, Jeanyves PotvinAbstract:This paper describes an exact [epsilon]-constraint method for bi-objective combinatorial optimization problems with integer objective values. This method tackles multi-objective optimization problems by solving a series of single objective subproblems, where all but one objectives are transformed into constraints. We show in this paper that the Pareto front of bi-objective problems can be efficiently generated with the [epsilon]-constraint method. Furthermore, we describe heuristics based on information gathered from previous subproblems that significantly speed up the method. This approach is used to find the exact Pareto front of the Traveling Salesman Problem with Profits, a variant of the Traveling Salesman Problem in which a profit or prize value is associated with each vertex. The goal here is to visit a subset of vertices while addressing two conflicting objectives: maximize the collected prize and minimize the travel costs. We report the first exact results for this problem on instances derived from classical Vehicle Routing and Traveling Salesman Problem instances with up to 150 vertices. Results on approximations of the Pareto front obtained from a variant of our exact algorithm are also reported.
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Traveling Salesman Problems with Profits
Transportation Science, 2005Co-Authors: Dominique Feillet, Pierre Dejax, Michel GendreauAbstract:Traveling Salesman problems with profits (TSPs with profits) are a generalization of the Traveling Salesman problem (TSP), where it is not necessary to visit all vertices. A profit is associated with each vertex. The overall goal is the simultaneous optimization of the collected profit and the travel costs. These two optimization criteria appear either in the objective function or as a constraint. In this paper, a classification of TSPs with profits is proposed, and the existing literature is surveyed. Different classes of applications, modeling approaches, and exact or heuristic solution techniques are identified and compared. Conclusions emphasize the interest of this class of problems, with respect to applications as well as theoretical results.
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new insertion and postoptimization procedures for the Traveling Salesman problem
Operations Research, 1992Co-Authors: Michel Gendreau, Alain Hertz, Gilbert LaporteAbstract:This paper describes a new insertion procedure and a new postoptimization routine for the Traveling Salesman problem. The combination of the two methods results in an efficient algorithm (GENIUS) which outperforms known alternative heuristics in terms of solution quality and computing time.
Jeanfrancois Berube - One of the best experts on this subject based on the ideXlab platform.
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an exact e constraint method for bi objective combinatorial optimization problems application to the Traveling Salesman problem with profits
European Journal of Operational Research, 2009Co-Authors: Jeanfrancois Berube, Michel Gendreau, Jeanyves PotvinAbstract:Abstract This paper describes an exact ϵ -constraint method for bi-objective combinatorial optimization problems with integer objective values. This method tackles multi-objective optimization problems by solving a series of single objective subproblems, where all but one objectives are transformed into constraints. We show in this paper that the Pareto front of bi-objective problems can be efficiently generated with the ϵ -constraint method. Furthermore, we describe heuristics based on information gathered from previous subproblems that significantly speed up the method. This approach is used to find the exact Pareto front of the Traveling Salesman Problem with Profits, a variant of the Traveling Salesman Problem in which a profit or prize value is associated with each vertex. The goal here is to visit a subset of vertices while addressing two conflicting objectives: maximize the collected prize and minimize the travel costs. We report the first exact results for this problem on instances derived from classical Vehicle Routing and Traveling Salesman Problem instances with up to 150 vertices. Results on approximations of the Pareto front obtained from a variant of our exact algorithm are also reported.
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an exact epsilon constraint method for bi objective combinatorial optimization problems application to the Traveling Salesman problem with profits
European Journal of Operational Research, 2009Co-Authors: Jeanfrancois Berube, Michel Gendreau, Jeanyves PotvinAbstract:This paper describes an exact [epsilon]-constraint method for bi-objective combinatorial optimization problems with integer objective values. This method tackles multi-objective optimization problems by solving a series of single objective subproblems, where all but one objectives are transformed into constraints. We show in this paper that the Pareto front of bi-objective problems can be efficiently generated with the [epsilon]-constraint method. Furthermore, we describe heuristics based on information gathered from previous subproblems that significantly speed up the method. This approach is used to find the exact Pareto front of the Traveling Salesman Problem with Profits, a variant of the Traveling Salesman Problem in which a profit or prize value is associated with each vertex. The goal here is to visit a subset of vertices while addressing two conflicting objectives: maximize the collected prize and minimize the travel costs. We report the first exact results for this problem on instances derived from classical Vehicle Routing and Traveling Salesman Problem instances with up to 150 vertices. Results on approximations of the Pareto front obtained from a variant of our exact algorithm are also reported.
Amin Saberi - One of the best experts on this subject based on the ideXlab platform.
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an o log n log log n approximation algorithm for the asymmetric Traveling Salesman problem
Operations Research, 2017Co-Authors: Arash Asadpour, Shayan Oveis Gharan, Michel X Goemans, Aleksander Mądry, Amin SaberiAbstract:We present a randomized O(log n/log log n)-approximation algorithm for the asymmetric Traveling Salesman problem (ATSP). This provides the first asymptotic improvement over the long-standing Θ(log n)-approximation bound stemming from the work of Frieze et al. (1982) [Frieze AM, Galbiati G, Maffioki F (1982) On the worst-case performance of some algorithms for the asymmetric Traveling Salesman problem. Networks 12(1):23–39]. The key ingredient of our approach is a new connection between the approximability of the ATSP and the notion of so-called thin trees. To exploit this connection, we employ maximum entropy rounding—a novel method of randomized rounding of LP relaxations of optimization problems. We believe that this method might be of independent interest.
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an o log n log log n approximation algorithm for the asymmetric Traveling Salesman problem
Symposium on Discrete Algorithms, 2010Co-Authors: Arash Asadpour, Shayan Oveis Gharan, Michel X Goemans, Aleksander Mądry, Amin SaberiAbstract:We consider the Asymmetric Traveling Salesman problem for costs satisfying the triangle inequality. We derive a randomized algorithm which delivers a solution within a factor O(log n/ log log n) of the optimum with high probability.
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the asymmetric Traveling Salesman problem on graphs with bounded genus
arXiv: Data Structures and Algorithms, 2009Co-Authors: Shayan Oveis Gharan, Amin SaberiAbstract:We give a constant factor approximation algorithm for the asymmetric Traveling Salesman problem when the support graph of the solution of the Held-Karp linear programming relaxation has bounded orientable genus.
Martin W P Savelsbergh - One of the best experts on this subject based on the ideXlab platform.
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dynamic discretization discovery for solving the time dependent Traveling Salesman problem with time windows
Transportation Science, 2020Co-Authors: Mike Hewitt, Natashia Boland, Martin W P SavelsberghAbstract:We present a new solution approach for the time-dependent Traveling Salesman problem with time windows. This problem considers a Salesman who departs from his home, has to visit a number of cities ...
