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A greedy heuristic and a lower bound on a nonlinear stochastic TSP with partially satisfied node demand coverage constraint

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  • Murat Cal
  • Senol Altan

Abstract

The combinatorial travelling salesman problem (TSP) has driven researchers to find faster ways to solve the problem in reasonable times. As a result, researchers modified and created new TSP combinations such as multi-objective TSP or TSP with stochastic constraints. One of these constraints is the node demand coverage constraint. It makes sure that the demand of each node is satisfied in a route. In this study, we re-modify the node demand coverage constraint to be satisfied by some percentage of the time. This approach is more realistic because a node can be visited without covering its demand, allowing the missing of some nodes during the demand covering process while making our model nonlinear. We then provide a greedy heuristic in MATLAB and a lower bound determination procedure for this model and experiment with some predefined datasets.

Suggested Citation

  • Murat Cal & Senol Altan, 2023. "A greedy heuristic and a lower bound on a nonlinear stochastic TSP with partially satisfied node demand coverage constraint," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 26(3), pages 308-326.
    • Handle: RePEc:ids:ijmore:v:26:y:2023:i:3:p:308-326
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