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The ordered clustered travelling salesman problem: a hybrid genetic algorithm.

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  • 1Department of Computer Science, Al Imam Mohammad Ibn Saud Islamic University (IMSIU), P.O. Box 5701, Riyadh 11432, Saudi Arabia.

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A new hybrid genetic algorithm effectively solves the ordered clustered travelling salesman problem, offering better solutions faster than existing methods for complex routing and sequencing tasks.

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Area of Science:

  • Operations Research
  • Combinatorial Optimization
  • Computer Science

Background:

  • The ordered clustered travelling salesman problem (OCTSP) is an NP-hard variant of the travelling salesman problem.
  • It involves finding a low-cost Hamiltonian tour with contiguous cluster visits in a predefined order.
  • OCTSP has practical applications in transportation and sequencing.

Purpose of the Study:

  • To develop an efficient heuristic algorithm for solving the OCTSP.
  • To improve upon existing methods for finding optimal or near-optimal solutions.

Main Methods:

  • A hybrid genetic algorithm (GA) was developed.
  • The GA incorporates sequential constructive crossover, 2-opt search, and local search techniques.
  • The algorithm was tested on asymmetric and symmetric TSPLIB instances.

Main Results:

  • The proposed hybrid GA demonstrated superior performance compared to two existing algorithms.
  • The algorithm achieved high solution quality and reduced computational time.
  • Effectiveness was validated across various TSPLIB instances of differing sizes.

Conclusions:

  • The developed hybrid GA is a highly effective heuristic for the OCTSP.
  • This approach offers significant improvements in solution quality and computational efficiency.
  • The findings are relevant for practical transportation and sequencing optimization problems.