The mean value of a fuzzy number
Fuzzy Sets and Systems - Fuzzy Numbers
A study of the ranking function approach through mean values
Fuzzy Sets and Systems
The expected value of a fuzzy number
Fuzzy Sets and Systems
A new approach to some possibilistic linear programming problems
Fuzzy Sets and Systems
Possibilistic linear programming for managing interest rate risk
Fuzzy Sets and Systems
Ranking and defuzzification methods based on area compensation
Fuzzy Sets and Systems
Fuzzy Sets and Systems - Fuzzy mathematical programming
The spatial and temporal consolidation of returned products in a closed-loop supply chain network
Computers and Industrial Engineering - Special issue: Logistics and supply chain management
A bi-objective reverse logistics network analysis for post-sale service
Computers and Operations Research
Fuzzy optimization for supply chain planning under supply, demand and process uncertainties
Fuzzy Sets and Systems
A memetic algorithm for bi-objective integrated forward/reverse logistics network design
Computers and Operations Research
MRP with flexible constraints: A fuzzy mathematical programming approach
Fuzzy Sets and Systems
A stochastic model for forward-reverse logistics network design under risk
Computers and Industrial Engineering
Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty
Computers and Industrial Engineering
Capacitated location-routing problem with time windows under uncertainty
Knowledge-Based Systems
Resilient closed-loop supply chain network design based on patent protection
International Journal of Computer Applications in Technology
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The design of closed-loop supply chain networks has attracted more attention in recent years according to business and environmental factors. The significance of accounting for uncertainty and risk in such networks spurs an interest to develop appropriate decision making tools to cope with uncertain and imprecise parameters in closed-loop supply chain network design problems. This paper proposes a bi-objective possibilistic mixed integer programming model to deal with such issues. The proposed model integrates the network design decisions in both forward and reverse supply chain networks, and also incorporates the strategic network design decisions along with tactical material flow ones to avoid the sub-optimalities led from separated design in both parts. To solve the proposed possibilistic optimization model, an interactive fuzzy solution approach is developed by combining a number of efficient solution approaches from the recent literature. Numerical experiments are conducted to demonstrate the significance and applicability of the developed possibilistic model as well as the usefulness of the proposed solution approach.