1. Comparison of steepest ascent hill climbing algorithm and genetic algorithm in finding billing collector path (ACC Medan).
- Author
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Rachmawati, Dian, Selvida, Desilia, and Nabilla, Vika
- Subjects
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GENETIC algorithms , *AUTOMOBILE loans , *STAIR climbing , *PURCHASING power , *FINANCE companies , *SUPPLY & demand , *METAHEURISTIC algorithms - Abstract
Nowadays, because of the high demand for car transportation, not everyone has the purchasing power of cash, and people sometimes pay for it on credit. ACC is a finance company that acts as a facilitator for car loan financing. ACC collects car loans through collectors who are assigned an area in Medan City and also the address of the customer who will be billed in installments. To maximize the installment collection process, the collector's journey needs to be optimized. A metaheuristic algorithm can solve the collector-collection trip optimization problem. The metaheuristic algorithm used to solve this problem is the Steepest Ascent Hill Climbing algorithm and the genetic algorithm to find the optimum route from the collector billing path. After the two algorithms are implemented and tested, the final result of this research is the complexity of the Steepest Ascent Hill Climbing algorithm is θ(n) with a running time of 429.1936 ms on a 5-point test, while the complexity of the genetic algorithm is θ(n3) with a running time of 8921.8021 ms on a 5-point test. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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