An Application of Binary Cuckoo Search Algorithm to Orienteering Problem

Giovano Alberto, Alfian Tan


This research applies the cuckoo search metaheuristics model to find solutions to the Orienteering Problem (OP). The OP formulation is useful to model a situation in which someone wants to determine an optimal city route that is subject to a specified time constraint. OP can be categorized into NP Hard Problem which takes a very long time to analytically find the optimal solution as the number of entities involved increases. Therefore, metaheuristics often become an option to deal with this situation. A cuckoo search model based algorithm is developed in this research. An adjustment for discrete combinatorial problem is performed by adopting an idea of binary cuckoo search method. In addition, three types of local search methods are considered to improve the searching performance. This algorithm can eventually find better solutions for some of the 18 cases than two other benchmarked algorithms. Furthermore, experiment on model parameters shows that the worse nest fraction (P_alpha) affects the quality of solutions obtained.


Cuckoo Search; Orienteering Problem; NP-Hard Problem; Discrete Optimization

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