An interactive fuzzy programming system
Fuzzy Sets and Systems
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Synchronized Development of Production, Inventory, and Distribution Schedules
Transportation Science
Material Requirement Planning with fuzzy constraints and fuzzy coefficients
Fuzzy Sets and Systems
Fuzzy-genetic approach to aggregate production-distribution planning in supply chain management
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Fuzzy optimization for supply chain planning under supply, demand and process uncertainties
Fuzzy Sets and Systems
MRP with flexible constraints: A fuzzy mathematical programming approach
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
Business analytics in supply chains - The contingent effect of business process maturity
Expert Systems with Applications: An International Journal
A random fuzzy minimum spanning tree problem through a possibility-based value at risk model
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An integrated supply chain network design problem for bidirectional flows
Expert Systems with Applications: An International Journal
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - FUZZYSS'2011: 2nd International Fuzzy Systems Symposium
Information Sciences: an International Journal
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An efficient integration of production and distribution plans into a unified framework is critical to achieving competitive advantage. This paper addresses the production and distribution planning problem in a supply chain system that involves the allocation of production volumes among the different production lines in the manufacturing plants, and the delivery of the products to the distribution centers. An integrated optimization model for production and distribution planning is proposed, with the aimed of optimally coordinating important and interrelated logistics decisions. However, a real supply chain operates in a highly dynamic and uncertain environment. Therefore, this model is transformed into fuzzy models taking into account the fuzziness in the capacity constraints, and the aspiration level of costs using different aggregation operators. The applicability and flexibility of the proposed models are illustrated through a case study in consumer goods industry.