Remy Dupas

Work place: Univ. Bordeaux, CNRS, IMS, UMR 5218, 33405 Talence, France



Research Interests: Computational Science and Engineering, Combinatorial Optimization, Engineering


Rémy Dupas was born in 1961. He is a professor at University of Bordeaux. Scientific interests: operational research, combinatorial optimization, industrial engineering, production and transportation problems (scheduling, supply chain planning and vehicle routing).

Author Articles
Scheduling Freight Trains in Rail-rail Transshipment Yards with Train Arrangements

By Igor Grebennik Remy Dupas Oleksandr Lytvynenko Inna Urniaieva

DOI:, Pub. Date: 8 Oct. 2017

A problem of scheduling freight trains in rail-rail transshipment yards is considered. It is solved at a deeper level compared to original papers dedicated to this problem: besides scheduling service slots for trains, this article additionally solves a problem of assigning every train to a railway track. A mathematical model and a solving method for this problem are given. A key feature of the given mathematical model is that it doesn’t use Boolean variables but rather operates with combinatorial objects (tuples of permutations). The solution method is also based on generation of combinatorial sets, which is quite an unusual approach for solving such problems.

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An Heuristic Approach to Solving the one-to-one Pickup and Delivery Problem with Threedimensional Loading Constraints

By Remy Dupas Igor Grebennik Oleksandr Lytvynenko Oleksij Baranov

DOI:, Pub. Date: 8 Oct. 2017

A mathematical model and a solving strategy for the Pickup and Delivery Problem with three-dimensional loading constraints regarding a combinatorial configuration instead of a traditional approach that utilizes Boolean variables is proposed. A traditional one-to-one Pickup and Delivery Problem in a combination with a problem of packing transported items into vehicles by means of the proposed combinatorial generation algorithm is solved.

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A Parallel Ring Method for Solving a Large-scale Traveling Salesman Problem

By Roman Bazylevych Bohdan Kuz Roman Kutelmakh Remy Dupas Bhanu Prasad Yll Haxhimusa Lubov Bazylevych

DOI:, Pub. Date: 8 May 2016

A parallel approach for solving a large-scale Traveling Salesman Problem (TSP) is presented. The problem is solved in four stages by using the following sequence of procedures: decomposing the input set of points into two or more clusters, solving the TSP for each of these clusters to generate partial solutions, merging the partial solutions to create a complete initial solution M0, and finally optimizing this solution. Lin-Kernighan-Helsgaun (LKH) algorithm is used to generate the partial solutions. The main goal of this research is to achieve speedup and good quality solutions by using parallel calculations. A clustering algorithm produces a set of small TSP problems that can be executed in parallel to generate partial solutions. Such solutions are merged to form a solution, M0, by applying the "Ring" method. A few optimization algorithms were proposed to improve the quality of M0 to generate a final solution Mf. The loss of quality of the solution by using the developed approach is negligible when compared to the existing best-known solutions but there is a significant improvement in the runtime with the developed approach. The minimum number of processors that are required to achieve the maximum speedup is equal to the number of clusters that are created.

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