Displaying similar documents to “Large neighborhood improvements for solving car sequencing problems”

Consistency checking within local search applied to the frequency assignment with polarization problem

Michel Vasquez, Audrey Dupont, Djamal Habet (2003)

RAIRO - Operations Research - Recherche Opérationnelle

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We present a hybrid approach for the Frequency Assignment Problem with Polarization. This problem, viewed as Max-CSP, is treated as a sequence of decision problems, CSP like. The proposed approach combines the Arc-Consistency techniques with a performed Tabu Search heuristic. The resulting algorithm gives some high quality solutions and has proved its robustness on instances with approximately a thousand variables and nearly ten thousand constraints.

France Telecom workforce scheduling problem: a challenge

Sebastian Pokutta, Gautier Stauffer (2009)

RAIRO - Operations Research

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In this paper, we describe the methodology used to tackle France Telecom workforce scheduling problem (the subject of the Roadef Challenge 2007) and we report the results obtained on the different data sets provided for the competition. Since the problem at hand appears to be NP-hard and due to the high dimensions of the instance sets, we use a two-step heuristical approach. We first devise a problem-tailored heuristic that provides good feasible solutions and then we use a meta-heuristic...

Enumerating the Set of Non-dominated Vectors in Multiple Objective Integer Linear Programming

John Sylva, Alejandro Crema (2008)

RAIRO - Operations Research

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An algorithm for enumerating all nondominated vectors of multiple objective integer linear programs is presented. The method tests different regions where candidates can be found using an auxiliary binary problem for tracking the regions already explored. An experimental comparision with our previous efforts shows the method has relatively good time performance.

Adaptive search heuristics for the generalized assignment problem.

Helena Ramalhinho Lourenço, Daniel Serra (2002)

Mathware and Soft Computing

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The Generalized Assignment Problem consists of assigning a set of tasks to a set of agents at minimum cost. Each agent has a limited amount of a single resource and each task must be assigned to one and only one agent, requiring a certain amount of the agent's resource. We present the application of a MAX-MIN Ant System (MMAS) and a greedy randomized adaptive search procedure (GRASP) to the generalized assignment problem based on hybrid approaches. The MMAS heuristic can be seen as an...