Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy Mathematical Programming: Methods and Applications
Fuzzy Mathematical Programming: Methods and Applications
Applying fuzzy goal programming to production/transportation planning decisions in a supply chain
International Journal of Systems Science
Computers and Industrial Engineering
TQM consultant selection in SMEs with TOPSIS under fuzzy environment
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Computers and Industrial Engineering
Fuzzy multi-objective project management decisions using two-phase fuzzy goal programming approach
Computers and Industrial Engineering
Distribution planning decisions using interactive fuzzy multi-objective linear programming
Fuzzy Sets and Systems
Fuzzy hierarchical production planning (with a case study)
Fuzzy Sets and Systems
A fuzzy integrated methodology for evaluating conceptual bridge design
Expert Systems with Applications: An International Journal
Multi-objective aggregate production planning with fuzzy parameters
Advances in Engineering Software
Application of fuzzy sets to manufacturing/distribution planning decisions in supply chains
Information Sciences: an International Journal
The LTOPSIS: An alternative to TOPSIS decision-making approach for linguistic variables
Expert Systems with Applications: An International Journal
Analytical study on multi-product production planning with outsourcing
Computers and Operations Research
Mathematical and Computer Modelling: An International Journal
Integrating workers' differences into workforce planning
Computers and Industrial Engineering
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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This study develops a fuzzy multi-objective linear programming (FMOLP) model for solving the multiproduct aggregate production planning (APP) decision problem in a fuzzy environment. The proposed model attempts to minimize total production costs, carrying and backordering costs and rates of changes in labor levels considering inventory level, labor levels, capacity, warehouse space and the time value of money. A numerical example demonstrates the feasibility of applying the proposed model to APP problem. Its advantages are also discussed. The proposed model yields a compromise solution and the decision maker's overall levels of satisfaction. In particular, in contrast to other APP models, several significant characteristics of the proposed model are presented.