Displaying similar documents to “A comparative study of three different mathematical methods for solving the unit commitment problem.”

Scheduling electric power generators using particle swarm optimization combined with the lagrangian relaxation method

Huseyin Balci, Jorge Valenzuela (2004)

International Journal of Applied Mathematics and Computer Science

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This paper describes a procedure that uses particle swarm optimization (PSO) combined with the Lagrangian Relaxation (LR) framework to solve a power-generator scheduling problem known as the unit commitment problem (UCP). The UCP consists of determining the schedule and production amount of generating units within a power system subject to operating constraints. The LR framework is applied to relax coupling constraints of the optimization problem. Thus, the UCP is separated into independent...

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.

An algorithm for solving multiple objective integer linear programming problem

Moncef Abbas, Djamal Chaabane (2002)

RAIRO - Operations Research - Recherche Opérationnelle

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In the present paper a complete procedure for solving Multiple Objective Integer Linear Programming Problems is presented. The algorithm can be regarded as a corrected form and an alternative to the method that was proposed by Gupta and Malhotra. A numerical illustration is given to show that this latter can miss some efficient solutions. Whereas, the algorithm stated bellow determines all efficient solutions without missing any one.