A greedy heuristic and a lower bound on a nonlinear stochastic TSP with partially satisfied node demand coverage constraint
by Murat Cal; Senol Altan
International Journal of Mathematics in Operational Research (IJMOR), Vol. 26, No. 3, 2023

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.

Online publication date: Tue, 14-Nov-2023

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