The ant colony optimization meta-heuristic
New ideas in optimization
Competitive and Cooperative Inventory Policies in a Two-Stage Supply Chain
Management Science
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A decision framework for the analysis of green supply chain contracts: An evolutionary game approach
Expert Systems with Applications: An International Journal
Swarm intelligence supported e-remanufacturing
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Hi-index | 12.06 |
Lumpy demand forces capacity planners to maximize the profit of individual factories as well as simultaneously take advantage of outsourcing from its supply chain and even competitors. This study examines a business model of capacity planning and resource allocation in which consists of two profit-centered factories. We propose an ant algorithm for solving a set of non-linear mixed integer programming models of the addressed problem with different economic objectives and constraints of negotiating parties. An individual factory applies a specific resource planning policy to improve its objective while borrowing resource capacity from its peer factory or lending extra capacity of resources to the other. The proposed method allows a mutually acceptable capacity plan of resources for a set of customer tasks to be allocated by two negotiating parties, each with private information regarding company objectives, cost and price. Experiment results reveal that near optimal solutions for both of isolated (a single factory) and negotiation-based (between the two factories) environments are obtained.