New Frontiers in Communication and Intelligent Systems
An Opposition-based Genetic Algorithm for Multi-Path Routing Problem with Risk
Authors: Somnath Maji, Samir Maity, Debasis Giri and Manoranjan Maiti
Publishing Date: 23-12-2022
ISBN: 978-81-95502-00-4
Abstract
Here, we propose an Opposition-based Genetic Algorithm (OBGA) to design and solve a Multi-path Routing Problem with Risk (MPRPwR). We consider a person purchasing some precious products (jewellery, electronic gadgets, etc.) from different shops/wholesalers at different places with predetermined demands and having some risks of theft along the routes of routing. Here, two types of risks-one depending on distance and amount of valuable materials and other pathwise are considered. Thus the problem is to find a round trip starting from and ending at the depot after visiting all the shops and collecting the precious products at a minimum system cost under a risk constraint. Here we introduce different alternate paths for travel between the shops. To solve it, OBGA with probabilistic selection, comparison crossover and generation dependent opposition-based mutation is developed and tested against some standard test functions. The effectiveness of our model (MPRPwR) solved by the proposed algorithm (OBGA) is illustrated. A standard Genetic Algorithm (SGA) is used for comparison with OBGA. In particular cases, the model has been solved with a single path and path-dependent risks.
Keywords
Opposition-based learning, Genetic Algorithm (GA), Cash in transit, Risk of theft, Fixed charge
Cite as
Somnath Maji, Samir Maity, Debasis Giri and Manoranjan Maiti, "An Opposition-based Genetic Algorithm for Multi-Path Routing Problem with Risk", In: Rahul Srivastava and Aditya Kr. Singh Pundir (eds), New Frontiers in Communication and Intelligent Systems, SCRS, India, 2022, pp. 727-746. https://doi.org/10.52458/978-81-95502-00-4-73