The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Sandra Ulrich Ngueveu - One of the best experts on this subject based on the ideXlab platform.
-
a matheuristic with fixed sequence reoptimization for a real life inventory routing problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life inventory routing problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two r...
-
A Matheuristic with Fixed-Sequence Reoptimization for a Real-Life Inventory Routing Problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life Inventory Routing Problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two ran-domized greedy algorithms, and a column-generation based heuristic. In particular, the paper discusses the performance of the fixed-sequence Mathematical Program, which considers a fixed sequence of customer visits and aims at (re)optimizing partial solutions by modifying arrival times and delivered or loaded quantities. Experiments show that the proposed algorithm for the fixed-sequence sub-problem is efficient as a post-optimization process and is even able to improve the best solutions obtained during the Challenge.
Laia Ferrer - One of the best experts on this subject based on the ideXlab platform.
-
an improved Mathematical Program to solve the simple assembly line balancing problem
International Journal of Production Research, 2009Co-Authors: Rafael Pastor, Laia FerrerAbstract:The simple assembly line balancing problem (SALBP) has been extensively examined in the literature. Various Mathematical Programs have been developed to solve SALBP type-1 (minimising the number of workstations, m, for a given cycle time, ct) and SALBP type-2 (minimising ct given m). Usually, an initial pre-process is carried out to calculate the range of workstations to which a task i may be assigned, in order to reduce the number of variables of task–workstation assignment. This paper presents a more effective Mathematical Program than those released to date to solve SALBP-1 and SALBP-2. The key idea is to introduce additional constraints in the Mathematical Program, based on the fact that the range of workstations to which a task i may be assigned depends either on the upper bound on the number of workstations or on the upper bound on the cycle time (for SALBP-1 and SALBP-2, respectively). A computational experiment was carried out and the results reveal the superiority of the Mathematical Program prop...
-
An improved Mathematical Program to solve the simple assembly line balancing problem
International Journal of Production Research, 2009Co-Authors: Rafael Pastor, Laia FerrerAbstract:The Simple Assembly Line Balancing Problem (SALBP) has been extensively examined in the literature. Various Mathematical Programs have been developed to solve SALBP type-1 (minimizing the number of workstations, m, for a given cycle time, ct) and SALBP type-2 (minimizing ct given m). Usually, an initial pre-process is carried out to calculate the range of workstations to which a task i may be assigned, in order to reduce the number of variables of task-workstation assignment. This paper presents a more effective Mathematical Program than those released to date to solve SALBP-1 and SALBP-2. The key idea is to introduce additional constraints in the Mathematical Program, based on the fact that the range of workstations to which a task i may be assigned depends either on the upper bound on the number of workstations or on the upper bound on the cycle time (for SALBP-1 and SALBP-2, respectively). A computational experiment was carried out and the results reveal the superiority of the Mathematical Program proposed.
Christian Artigues - One of the best experts on this subject based on the ideXlab platform.
-
a matheuristic with fixed sequence reoptimization for a real life inventory routing problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life inventory routing problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two r...
-
A Matheuristic with Fixed-Sequence Reoptimization for a Real-Life Inventory Routing Problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life Inventory Routing Problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two ran-domized greedy algorithms, and a column-generation based heuristic. In particular, the paper discusses the performance of the fixed-sequence Mathematical Program, which considers a fixed sequence of customer visits and aims at (re)optimizing partial solutions by modifying arrival times and delivered or loaded quantities. Experiments show that the proposed algorithm for the fixed-sequence sub-problem is efficient as a post-optimization process and is even able to improve the best solutions obtained during the Challenge.
Cyril Briand - One of the best experts on this subject based on the ideXlab platform.
-
a matheuristic with fixed sequence reoptimization for a real life inventory routing problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life inventory routing problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two r...
-
A Matheuristic with Fixed-Sequence Reoptimization for a Real-Life Inventory Routing Problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life Inventory Routing Problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two ran-domized greedy algorithms, and a column-generation based heuristic. In particular, the paper discusses the performance of the fixed-sequence Mathematical Program, which considers a fixed sequence of customer visits and aims at (re)optimizing partial solutions by modifying arrival times and delivered or loaded quantities. Experiments show that the proposed algorithm for the fixed-sequence sub-problem is efficient as a post-optimization process and is even able to improve the best solutions obtained during the Challenge.
Nicolas Jozefowiez - One of the best experts on this subject based on the ideXlab platform.
-
a matheuristic with fixed sequence reoptimization for a real life inventory routing problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life inventory routing problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two r...
-
A Matheuristic with Fixed-Sequence Reoptimization for a Real-Life Inventory Routing Problem
Transportation Science, 2020Co-Authors: Christian Artigues, Cyril Briand, Nicolas Jozefowiez, Sandra Ulrich NgueveuAbstract:This paper proposes a matheuristic for solving a real-life Inventory Routing Problem introduced in the ROADEF/EURO Challenge 2016. The method integrates a fixed-sequence Mathematical Program, two ran-domized greedy algorithms, and a column-generation based heuristic. In particular, the paper discusses the performance of the fixed-sequence Mathematical Program, which considers a fixed sequence of customer visits and aims at (re)optimizing partial solutions by modifying arrival times and delivered or loaded quantities. Experiments show that the proposed algorithm for the fixed-sequence sub-problem is efficient as a post-optimization process and is even able to improve the best solutions obtained during the Challenge.