Probabilistic local search algorithms for concave cost transportation network problems

Article Abstract:

Concave cost transportation problems are usually characterized as NP-hard. Thus, cost functions are often simplified as linear to facilitate problem solving. However, linear cost functions may not represent actual operations, which usually results in reduced operational performance. Simulated annealing and threshold accepting were used to develop a number of heuristics that would efficiently solve these concave cost transportation network problems.

Methods, Models, Usage, Algorithms, Transportation, Simulated annealing (Mathematics)

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Fixing variables and generating classical cutting planes when using an interior point branch and cut method to solve integer programming problems

Article Abstract:

An interior point approach to solving linear programming relaxations of cutting problems attained through the application of branch and cut techniques for integer programming problems. The method involved fixing variables using the dual feasible solution and generating Gomory-like cutting planes and lift-and-project cutting planes from the objective function without resolving the relaxation to optimality.

Research, Case studies, Integer programming, Cutting

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