Abstract⎯In this paper, we introduce a fuzzy Economic Production Quantity (EPQ) model with defective products that can be repaired. In this model, we consider a fuzzy opportunity cost, trapezoidal fuzzy costs and quantities into the traditional production inventory model. We use Function Principle and Graded Mean Integration Representation Method to find optimal economic production quantity of the fuzzy production inventory model. Keywords⎯Fuzzy production inventory model, Economic production quantity, Function principle, Graded mean

Abstract: The paper considers the economic lot scheduling problem (ELSP) where production facility is assumed to deteriorate, owing to aging, with an increasing failure rate. The time to shift from an “in-control ” state to an “out-of-control ” state is assumed to be normally distributed. The system is scheduled to be inspected at the end of each production lot. If the process is found to be in an “out-of-control ” state, then corrective maintenance is performed to restore it to an “in-control ” state before the start of the next production run. Otherwise, preventive maintenance is carried out to enhance system reliability. The ELSP is formulated under the capacity constraint taking into account the quality related cost due to possible production of non-conforming items, process inspection, and maintenance costs. In order to find a feasible production schedule, both the common cycle and time-varying lot sizes approaches are utilized. © 2003 Wiley Periodicals, Inc.

This paper addresses the problem of scheduling economic lots in a multi-product single-machine environment. A mixed integer non-linear programming formulation is developed which finds the optimal sequence and economic lots. The model takes explicit account of initial inventories, setup times, allows setups to be scheduled at arbitrary epochs in continuous time and models backorders. To solve the problem we develop a hybrid approach, combining a genetic algorithm and linear programming. The approach is tested on a set of instances taken from the literature and compared with other approaches. The experimental results validate the quality of the solutions and the effectiveness of the proposed approach.

Abstract. In the real world, vague phenomenon is quite common in the production/inventory models. In order to process the vagueness, a production/inventory model that can be more closely related to the real vagueness and can take account of the vague factors that contribute to production costs, is required. The model must be extended or altered to fit in with the fuzzy situation. Since items with imperfect quality, during production or inventory procedure, are unavoidable, we also consider this situation. In order to treat the case in the vague environment, we propose a Fuzzy Economic Production Quantity (FEPQ) model with imperfect products that can be sold at a discount price. In this model, costs and quantities are expressed as trapezoidal fuzzy numbers. Moreover, we use Function Principle to manipulate arithmetical operations, Graded Mean Integration Representation method to defuzzify, and Kuhn-Tucker conditions to find the optimal economic production quantity of the fuzzy production inventory model. Finally, an application of an electronics industry example gives a satisfactory result.

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In this study the periodic review inventory models with partial lost sales caused by stock-out are considered, and the eects of increasing investment to reduce the lost sales rate are analyzed. Two models concerning to complete (normal distribution) and partial (distribu-tion free) information about the protection interval demand distribution are discussed. For each model, an algorithm is developed to nd the optimal investment strategy.

genetic algorithm for the economic lot-scheduling problem

1.1 Background of the study In the past twenty (20) years, technological advancements, international competitions and