No abstract

Purpose – The purpose of this paper is to propose an approach that integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning. Unsatisfied customers, information overload and high uncertainty are the main challenges that are faced by today’s supply chains. In addition, a few existing agent-based approaches are tied to real-world supply chain functions like supplier selection. These approaches are static and do not adequately take the qualitative and quantitative factors into consideration. Therefore, an agent-based framework is needed to address these issues. Design/methodology/approach – The proposed approach integrates three complementary perspectives, multi-agent systems, fuzzy logic and case-based reasoning, as a common framework. These perspectives were rarely used together as a common framework in previous studies. Furthermore, an exploratory case study in an office furniture company is undertaken to illustrate the value of the framework. Findings – The proposed agent-based framework evaluates supply offers based on customers’ preferences, recommends alternative products in the case of stock-out and provides a collaborative environment among agents who represent different supply chain entities. The proposed fuzzy case-based reasoning (F-CBR) approach reduces the information overload by organizing them into the relevant cases that causes less overall search between cases. In addition, its fuzzy aspect addresses the high uncertainty of supply chains, especially when there are different customers’ orders with different preferences. Research limitations/implications – The present study does not include the functions of inventory management and negotiation between agents. Furthermore, only the case description and case retrieval phases of the case-based reasoning approach are investigated, and the remaining phases like case retaining, case reusing and case revising are not included in the scope of this paper. Originality/value – This framework balances the interests of different supply chain structural elements where each of them is represented by a specific agent for better collaboration, decision-making and problem-solving in a multi-agent environment. In addition, the supplier selection and order gathering mechanisms are developed based on customers’ orders.

In any customer driven supply chain, the acquisition of customer knowledge can help companies to attain a competitive advantage in product innovation. Since the existing approaches have not considered this knowledge as a weighted factor in the case based supplier selection processes, this paper aims to present an agent-based framework for supplier selection based on the case-based reasoning approach. This framework uses customer knowledge to evaluate the price, volume, quality grade, and delivery date of supply materials and provide them with alternative products which are closest to their first order if it was out of stock. Based on the proposed framework, a numerical example of the known case study is illustrated for highlighting the effectiveness of the approach.

Supply Chain is a network of organizations and their associated activities that work together to create value for the customer. This paper aims to present comprehensive and systematic negotiation and recommendation framework for e-Supply Chain by using multi-agent approach. Such framework should receive suppliers material offers, rank the suppliers, and provide recommendations for customers. On behalf of the standard tasks like interface, recommendation, negotiation, and data retrieval, some agents have designed to use neural network for supplier ranking and classification for data filtering to reduce the information overload and enhance the negotiation ability of the agents. Besides, it would customize the information for users based on their interests.