An investigation of niche and species formation in genetic function optimization
Proceedings of the third international conference on Genetic algorithms
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy inventory without backorder for fuzzy order quantity and fuzzy total demand quantity
Computers and Operations Research
Inter-company comparison using modified TOPSIS with objective weights
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms for Control and Signal Processing
Genetic Algorithms for Control and Signal Processing
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolutionary Algorithms for Solving Multi-Objective Problems
Evolutionary Algorithms for Solving Multi-Objective Problems
Optimization of fuzzy production inventory models
Information Sciences—Applications: An International Journal
Combining convergence and diversity in evolutionary multiobjective optimization
Evolutionary Computation
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
The nature of niching: genetic algorithms and the evolution of optimal, cooperative populations
The nature of niching: genetic algorithms and the evolution of optimal, cooperative populations
Application of fuzzy multi-objective linear programming to aggregate production planning
Computers and Industrial Engineering
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
A displayed inventory model with L---R fuzzy number
Fuzzy Optimization and Decision Making
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Multi-objective learning via genetic algorithms
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Multiple replenishment orders in a continuous-review inventory system with lost sales
Operations Research Letters
Expert Systems with Applications: An International Journal
Review: A state-of the-art survey of TOPSIS applications
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
| Hi-index | 0.98 |
Multi-periodic inventory control problems are mainly studied employing one of two assumptions. The first is the continuous review, where depending on the inventory level, orders can be placed at any time, and the other is the periodic review, where orders can be placed only at the beginning of each period. In this paper, we relax these assumptions and assume that the time-periods between two replenishments are random fuzzy variables. While in the model of the problem at hand the decision variables are of integer type and there are space and service level constraints, for the shortages we consider a combination of back-order and lost-sales. We show the model of this problem to be an integer-nonlinear-programming type and in order to solve it, a hybrid method of Pareto, TOPSIS and Genetic Algorithm approach is used. At the end, a numerical example is given to demonstrate the applicability of the proposed methodology.