English, Article edition: Improving benders decomposition using a genetic algorithm Poojari, C.A.; Beasley, J.E.

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Physical Description
  • article
Language
  • English

Edition details

Title
  • Improving benders decomposition using a genetic algorithm
Author
  • Poojari, C.A.
  • Beasley, J.E.
Physical Description
  • article
Notes
  • We develop and investigate the performance of a hybrid solution framework for solving mixed-integer linear programming problems. Benders decomposition and a genetic algorithm are combined to develop a framework to compute feasible solutions. We decompose the problem into a master problem and a subproblem. A genetic algorithm along with a heuristic are used to obtain feasible solutions to the master problem, whereas the subproblem is solved to optimality using a linear programming solver. Over successive iterations the master problem is refined by adding cutting planes that are implied by the subproblem. We compare the performance of the approach against a standard Benders decomposition approach as well as against a stand-alone solver (Cplex) on MIPLIB test problems.
  • Genetic algorithm Benders decomposition Mixed-integer linear programs
  • RePEc:eee:ejores:v:199:y:2009:i:1:p:89-97
Language
  • English
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