Multi Agent Collaborative Search based on Tchebycheff decomposition

Multi Agent Collaborative Search based on Tchebycheff decomposition

This paper presents a novel formulation ofMulti Agent Collaborative Search, for multi-objective optimization, based on Tchebycheff decomposition. A population of agents combines heuristics that aim at exploring the search space both globally (social moves) and in a neighborhood of each agent (individualistic moves). In this novel formulation the selection process is based on a combination of Tc...

Dynamic configuration and collaborative scheduling in supply chains based on scalable multi-agent architecture

Due to diversified and frequently changing demands from customers, technological advances and global competition, manufacturers rely on collaboration with their business partners to share costs, risks and expertise. How to take advantage of advancement of technologies to effectively support operations and create competitive advantage is critical for manufacturers to survive. To respond to these...

Multi-objective Local Search Based on Decomposition

Collaborative Multi-Agent-based e-Commerce Framework

Software agents offer a promise to change electronic commerce trading by helping traders to purchase products based on their interests and preferences. E-commerce systems are increasingly recognizing the importance of giving additional value to customers by providing customized transactional experiences. We believe that increased support for collaboration is a logical next step in the evolution...

A Collaborative Multi-agent Based Workflow System

Agent based workflow systems are being discussed by many researchers for a long time. In this paper we present a new collaborative approach for workflow systems. Agents collaborate by forming social network such as societies. Various kinds of societies can exist and that facilitates cooperation and a communal effort towards group oriented problem solving. This framework would help us study the ...