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A Smart Structural Algorithm (SSA) Based on Infeasible Region to Solve Mixed Integer Problems

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  • Mohammad Hassan Salmani

    (Sharif University of Technology, Tehran, Iran)

  • Kourosh Eshghi

    (Sharif University of Technology, Tehran, Iran)

Abstract

Optimization is an important fields of study in science where researchers seek to make the best and most practical decisions. Solving real optimization problems is an intractable issue which calls for generating an approximate using meta-heuristic algorithms. This study proposes a meta-heuristic algorithm which mainly searches the infeasible region. In this approach, the authors start from an infeasible solution, and while they try to get near to the feasible region, they ensure that the best value is kept for the objective function. The algorithm examines the space in such terms as Infeasibility and Objective Functions, Neighborhood Limited Area, Random Smart Points, and the calculation of new solutions. The algorithm can convert an infeasible solution to an appropriate corresponding feasible solution by applying a simple mathematical methodology. Finally, to test the efficiency of our algorithm, a sample random MIP problem and a hard benchmark TSP instance are solved and discussed in detail.

Suggested Citation

  • Mohammad Hassan Salmani & Kourosh Eshghi, 2017. "A Smart Structural Algorithm (SSA) Based on Infeasible Region to Solve Mixed Integer Problems," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 8(1), pages 24-44, January.
    • Handle: RePEc:igg:jamc00:v:8:y:2017:i:1:p:24-44
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    Cited by:

    1. Mohammad Hassan Salmani & Kourosh Eshghi, 2017. "A Metaheuristic Algorithm Based on Chemotherapy Science: CSA," Journal of Optimization, Hindawi, vol. 2017, pages 1-13, February.

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