Fuzzy goal programming- an additive model
Fuzzy Sets and Systems
Ranking fuzzy numbers with integral value
Fuzzy Sets and Systems
Method for solving multiobjective aggregate production planning problem with fuzzy parameters
Proceedings of the 14th annual conference on Computers and industrial engineering
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
The relationship between goal programming and fuzzy programming
Fuzzy Sets and Systems
A generalization of fuzzy goal programming with preemptive structure
Computers and Operations Research
Application of fuzzy multi-objective linear programming to aggregate production planning
Computers and Industrial Engineering
Aggregate Production Planning Utilizing A Fuzzy Linear Programming
Journal of Integrated Design & Process Science
Fuzzy-genetic approach to aggregate production-distribution planning in supply chain management
Information Sciences: an International Journal
Compensatory operators in fuzzy linear programming with multiple objectives
Fuzzy Sets and Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Integrating workers' differences into workforce planning
Computers and Industrial Engineering
Scheduling with an outsourcing option on both manufacturer and subcontractors
Computers and Operations Research
Modeling and Pareto optimization of multi-objective order scheduling problems in production planning
Computers and Industrial Engineering
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In this study a hybrid (including qualitative and quantitative objectives) fuzzy multi objective nonlinear programming (H-FMONLP) model with different goal priorities will be developed for aggregate production planning (APP) problem in a fuzzy environment. Using an interactive decision making process the proposed model tries to minimize total production costs, carrying and back ordering costs and costs of changes in workforce level (quantitative objectives) and maximize total customer satisfaction (qualitative objective) with regarding the inventory level, demand, labor level, machines capacity and warehouse space. A real-world industrial case study demonstrates applicability of proposed model to practical APP decision problems. GENOCOP III (Genetic Algorithm for Numerical Optimization of Constrained Problems) has been used to solve final crisp nonlinear programming problem.