Fuzzy optimization: an appraisal
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
Fuzzy Sets and Systems - Fuzzy mathematical programming
Possibilistic programming in production planning of assemble-to-order environments
Fuzzy Sets and Systems
Supplier selection and order lot sizing modeling: A review
Computers and Operations Research
Efficient Production-Distribution System Design
Management Science
Inequality relation between fuzzy numbers and its use in fuzzy optimization
Fuzzy Sets and Systems
Distribution planning decisions using interactive fuzzy multi-objective linear programming
Fuzzy Sets and Systems
Computing efficient solutions to fuzzy multiple objective linear programming problems
Fuzzy Sets and Systems
MRP with flexible constraints: A fuzzy mathematical programming approach
Fuzzy Sets and Systems
Application of fuzzy minimum cost flow problems to network design under uncertainty
Fuzzy Sets and Systems
Fuzzy optimization for supply chain planning under supply, demand and process uncertainties
Fuzzy Sets and Systems
Optimizing material procurement planning problem by two-stage fuzzy programming
Computers and Industrial Engineering
Multi-strategy supplier selection for commodity sourcing
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
CIMMACS'09 Proceedings of the 8th WSEAS International Conference on Computational intelligence, man-machine systems and cybernetics
Expert Systems with Applications: An International Journal
Fuzzy hierarchical production planning (with a case study)
Fuzzy Sets and Systems
Fuzzy estimations and system dynamics for improving supply chains
Fuzzy Sets and Systems
Supply chain network modeling in a golf club industry via fuzzy linear programming approach
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Computers & Mathematics with Applications
WSEAS Transactions on Information Science and Applications
Model-based decision support system for water quality management under hybrid uncertainty
Expert Systems with Applications: An International Journal
Credibility-based fuzzy mathematical programming model for green logistics design under uncertainty
Computers and Industrial Engineering
A compensatory model for computing with words under discrete labels and incomplete information
Knowledge-Based Systems
Manufacturer's coordination mechanism for single-period supply chain problems with fuzzy demand
Mathematical and Computer Modelling: An International Journal
A possibilistic multiple objective pricing and lot-sizing model with multiple demand classes
Fuzzy Sets and Systems
Stackelberg game models between two competitive retailers in fuzzy decision environment
Fuzzy Optimization and Decision Making
Bi-objective supply chain planning in a fuzzy environment
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Information Sciences: an International Journal
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Providing an efficient production plan that integrates the procurement and distribution plans into a unified framework is critical to achieving competitive advantage. In this paper, we consider a supply chain master planning model consisting of multiple suppliers, one manufacturer and multiple distribution centers. We first propose a new multi-objective possibilistic mixed integer linear programming model (MOPMILP) for integrating procurement, production and distribution planning considering various conflicting objectives simultaneously as well as the imprecise nature of some critical parameters such as market demands, cost/time coefficients and capacity levels. Then, after applying appropriate strategies for converting this possibilistic model into an auxiliary crisp multi-objective linear model (MOLP), we propose a novel interactive fuzzy approach to solve this MOLP and finding a preferred compromise solution. The proposed model and solution method are validated through numerical tests. Computational results indicate that the proposed fuzzy method outperforms other fuzzy approaches and is very promising not only for solving our problem, but also for any MOLP model especially multi-objective mixed integer models.