Fuzzy goal programming- an additive model
Fuzzy Sets and Systems
Fuzzy geometric programming (I)
Fuzzy Sets and Systems
Polynomial geometric programming with L-R fuzzy coefficients
Fuzzy Sets and Systems
Chance constrained programming with fuzzy parameters
Fuzzy Sets and Systems
A note on chance constrained programming with fuzzy coefficients
Fuzzy Sets and Systems
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Fuzzy modeling in terms of surprise
Fuzzy Sets and Systems - Special issue: Interfaces between fuzzy set theory and interval analysis
Solving Large-Scale Fuzzy and Possibilistic Optimization Problems
Fuzzy Optimization and Decision Making
Linear programming under randomness and fuzziness
Fuzzy Sets and Systems
Fuzzy pricing and marketing planning model: A possibilistic geometric programming approach
Expert Systems with Applications: An International Journal
Solution of fuzzy integrated production and marketing planning based on extension principle
Computers and Industrial Engineering
A stochastic decision support system for economic order quantity problem
Advances in Fuzzy Systems
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In this paper, a multi-item economic order quantity (EOQ) model is considered in which the cost parameters are of fuzzy/hybrid nature under two types of resources - (a) resources as fuzzy quantities; (b) resources as fuzzy and fuzzy-random quantities. The unit cost depends on demand rate. The time horizon is taken to be infinite. We find the average cost for the model, which is a function of order quantity and demand rate and also of some hybrid parameters. When the resources are fuzzy quantities, the problem is transformed into its equivalent unconstrained deterministic form by using a surprise function for the constraints. The problem involving hybrid number is again equivalently rewritten as a multi-objective (minimization of the mean of the objective function and variance function of the distribution) inventory problem. Introducing new variables we transform the terms of the functions into signomial types. Using fuzzy multi-objective solution procedure we solve the problem through Geometric Programming approach. Sensitivity analysis has been performed to study the effect of different weights considered for mean objective function and variance function.