Decision support system

Supply chain

Dispose pattern

Engineering

Environmental economics

Business

Artificial intelligence

Economics

Marketing

Microeconomics

Ecology

Circular economy

Production (economics)

Supplier evaluation

Computer science

Operations research

Supply chain management

Waste management

Fuzzy logic

Sustainability

Selection (genetic algorithm)

Biology

Sustainable Production and Consumption

Supplier selection is an important and challenging problem in sustainable supply chain management. We propose a dynamic decision support system (DSS) for sustainable supplier selection in circular supply chains. Unlike the linear take-make-waste-dispose production systems, circular supply chains are nonlinear make-waste-recycle production systems with zero-waste vision. The proposed DSS allows users to customize and weight their economic, social, and circular criteria with a fuzzy best-worst method (BWM) and select the most suitable supplier with the fuzzy inference system (FIS). Machine learning is used to maintain and synthesize the criteria scores for the suppliers after each supplier selection engagement. We present a case study at a petrochemical holding company with a controlling interest over several subsidiary companies to demonstrate the applicability of the proposed approach.

A Dynamic Decision Support System for Sustainable Supplier Selection in Circular Economy