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Solution of Solid Traveling Purchaser Problem Using Efficient Genetic Algorithm with Probabilistic Selection and Multi-Parent Crossover Technique

Arindam Roy

Abstract


In this paper, I design a NP-hard optimization problem and solve this problem by developing a nature-based multi-parent crossover in genetic algorithm (GA). Initially, taking a set of markets, a depot and some products for each of which a positive demand is specified. Purchaser can purchase each product from a subset of markets only a given quantity, less than or equal to the required one, can be purchased at a given unit price. Traveling purchaser forms a cycle starting at and ending to the depot and visiting a subset of markets at a minimum traveling cost. Here, I consider multiple vehicle to visit different markets say solid TPP (STPP). The activeness of my model is illustrated by numerical examples.

Cite this Article

Arindam Roy. Solution of Solid Traveling Purchaser Problem Using Efficient Genetic Algorithm with Probabilistic Selection and Multi-Parent Crossover Technique. Research & Reviews: Discrete Mathematical Structures. 2018; 5(3):
20–26p.


Keywords


GA, TSP, TPP, Solid TSP and Solid TPP

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References


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