2 publications

• Published Subscription 7 Feb 2019

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

  By 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 …

  Published in Research & Reviews: Discrete Mathematical Structures · Vol. 5, Issue 3, 2018 · pp. 20–26 Read article →

• Published Subscription 29 Jul 2014

  A Production Inventory Model in a Random Planning Horizon Incorporating Learning Effects on Inventory Costs Under Inflation and Time Value of Money via Genetic Algorithm

  By Arindam Roy, Manas Kumar Maiti

  Abstract: A production inventory model for a new product is developed incorporating inflation and time value of money. It is assumed that lifetime of the product is random in nature and follows exponential distribution with a known mean. So planning horizon of the model is random in nature. Here learning effect on production and set-up cost is incorporated. Model is formulated to maximize the expected profit from the whole plan-ning horizon …

  Published in Journal of Artificial Intelligence Research & Advances · Vol. 1, Issue 2, 2014 · pp. 1–12 Read article →