Some Approaches for Fuzzy Multiobjective Programming Problems

In this paper we discuss two approaches to bring a balance between effectiveness and efficiency while solving a multiobjective programming problem with fuzzy objective functions. To convert the original fuzzy optimization problem into deterministic terms, the first approach makes use of the Nearest Interval Approximation Operator (Approximation approach) for fuzzy numbers and the second one takes advantage of an Embedding Theorem for fuzzy numbers (Equivalence approach). The resulting optimization problem related to the first approach is handled via Karush- Kuhn-Tucker like conditions for Pareto Optimality obtained for the resulting interval optimization problem. A Galerkin like scheme is used to tackle the deterministic counterpart associated to the second approach. Our approaches enable both faithful representation of reality and computational tractability. They are thus in sharp contrast with many existing methods that are either effective or efficient but not both. Numerical examples are also supplemented for the sake of illustration.

Multi-objective economic production quantity model for fully backlogged problem where demand depend on some conditions and permissible delay in payment

For any business, inventory system takes a monumental part. Keep this aspect in mind, we formulate multi-objective displayed EPQ model consider with non-instantaneous deteriorating things where production depends on demand and variable demand pattern depends on display self-space, selling price and frequency of advertisement of the item. The customers are more attracted to buy an item by observing self-space, selling price and advertisement. Imperfect materials are now and again come back to providers for a discount or credit. Here price discount is available for deteriorated and defective items. Holding cost varies with time where shortages are allowed and fully backlogged. Fuzzy environment touches the reality instead of the crisp environment. So, we assumed the cost components as Triangular Fuzzy Numbers and Nearest Interval Approximation Method is used to defuzzify the model. Finally, numerical examples as well as sketches are given to illustrate the model.

An approach to solve multi-objective linear production planning games with fuzzy parameters

In this research, n-person cooperative games, arising from multi-objective linear production planning problem with fuzzy parameters, are considered. It is assumed that the fuzzy parameters are fuzzy numbers. The fuzzy multi-objective game problem is transformed to a single-objective game problem by group AHP method. The obtained problem is converted to a problem with interval parameters by considering the nearest interval approximation of the fuzzy numbers. Then, optimistic and pessimistic core concepts are introduced. The payoff vectors of the players are obtained by the duality theorem of linear programming. Finally, validity and applicability of the method are illustrated by a practical example.

MATHEMATICAL PROGRAMMING PROBLEMS WITH SEVERAL FUZZY OBJECTIVE FUNCTIONS

In this paper we propose an approach for multiobjective programming problems with fuzzy number coefficients. The main idea behind our approach is to approximate involved fuzzy numbers by their respective nearest interval approximation counterparts. An algorithm that returns a nearest interval approximation to a given fuzzy number, plays a pivotal role in the proposed method. Our approach contrasts markedly with those based on deffuzification operators which replace a fuzzy set by a single real number leading to a loss of many important information. A numerical example is also provided for the sake of illustration.