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An Algorithm to Supply Chain Configuration Based on Ant System
Abstract
This work proposes a new approach, based on Ant Colony Optimisation (ACO), to configure Supply Chains (SC) so as to deliver orders on due date and at the minimum cost. For a set of orders, this approach determines which supplier to acquire components from and which manufacturer will produce the products as well as which transportation mode must be used to deliver products to customers. The aforementioned decisions are addressed by three modules. The data module stores all data relating to SC and models the SC. The optimization engine is a multi-agent framework called SC Configuration by ACO. This module implements the ant colony algorithm and generates alternative SC configurations. Ant-k agent configures a single SC travelling by the network created by the first agent. While Ant-k agent visits a stage, it selects an option to perform a stage based on the amount of pheromones and the cost and lead time of the option. We solve a note-book SC presented in literature. Our approach computes pareto sets with SC design which delivers product from 38 to 91 days.
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