FUZZY INVENTORY MODEL FOR ITEMS WITH WEIBULL DISTRIBUTION DETERIORATION, POWER DEMAND, LINEAR HOLDING COST, SALVAGE COST AND PARTIAL BACKLOGGING

The objective of this research article is to develop an inventory model which incorporates power pattern demand, Weibull distribution deterioration, shortages and partial backlogging of orders. Holding cost is taken as time dependent and deteriorated items are assumed to have a salvage value. The cost parameters are fuzzified and the total cost is defuzzified using Graded mean representation, signed distance and centroid methods. The values obtained by these methods are compared with the help of numerical examples. The convexity of the cost function is depicted graphically. Sensitivity analysis is performed to study the effect of change in some parameters. Keywords: Inventory, Power demand, Partial backlogging, Deterioration, Triangular Fuzzy Number, Defuzzification, Graded mean represented method, Signed Distance Method, centroid method

The World of Combinatorial Fuzzy Problems and the Efficiency of Fuzzy Approximation Algorithms

We re-examine a practical aspect of combinatorial fuzzy problems of various types, including search, counting, optimization, and decision problems. We are focused only on those fuzzy problems that take series of fuzzy input objects and produce fuzzy values. To solve such problems efficiently, we design fast fuzzy algorithms, which are modeled by polynomial-time deterministic fuzzy Turing machines equipped with read-only auxiliary tapes and write-only output tapes and also modeled by polynomial-size fuzzy circuits composed of fuzzy gates. We also introduce fuzzy proof verification systems to model the fuzzification of nondeterminism. Those models help us identify four complexity classes: Fuzzy-FPA of fuzzy functions, Fuzzy-PA and Fuzzy-NPA of fuzzy decision problems, and Fuzzy-NPAO of fuzzy optimization problems. Based on a relative approximation scheme targeting fuzzy membership degree, we formulate two notions of "reducibility" in order to compare the computational complexity of two fuzzy problems. These reducibility notions make it possible to locate the most difficult fuzzy problems in Fuzzy-NPA and in Fuzzy-NPAO.Comment: A4, 10pt, 10 pages. This extended abstract already appeared in the Proceedings of the Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS 2014) and 15th International Symposium on Advanced Intelligent Systems (ISIS 2014), December 3-6, 2014, Institute of Electrical and Electronics Engineers (IEEE), pp. 29-35, 201

Однопериодная модель управления запасами с непрерывным нечетким случайным спросом

The paper describes an algorithm for searching the optimal enterprise inventory capacity, where the demand for this resource is a fuzzy random variable. In particular, the case of continuously distributed demand with the expected value which is a triangular fuzzy number has been discussed. A numerical example is given to illustrate the model.У статті описано алгоритм пошуку оптимального обсягу запасу ресурсу підприємства, в якому попит на цей ресурс є нечіткою випадковою величиною. Зокрема, розглянуто випадок, коли закон розподілу випадкового попиту відомий або може бути оцінений на основі статистичних даних і математичне сподівання якого – нечітке трикутне число. Теоретичний матеріал проілюстровано числовим прикладом.В статье описан алгоритм поиска оптимального размера запаса ресурса предприятия, спрос на который является нечеткой случайной величиной. В частности, рассмотрен случай, когда закон распределения спроса известен или может быть оценен на основании статистических данных и математическое ожидание которого – нечеткое треугольное число. Теоретический материал проиллюстрирован числовым примером

An EPQ Model with Two-Component Demand under Fuzzy Environment and Weibull Distribution Deterioration with Shortages

A single-item economic production model is developed in which inventory is depleted not only due to demand but also by deterioration. The rate of deterioration is taken to be time dependent, and the time to deterioration is assumed to follow a two-parameter Weibull distribution. The Weibull distribution, which is capable of representing constant, increasing, and decreasing rates of deterioration, is used to represent the distribution of the time to deterioration. In many real-life situations it is not possible to have a single rate of production throughout the production period. Items are produced at different rates during subperiods so as to meet various constraints that arise due to change in demand pattern, market fluctuations, and so forth. This paper models such a situation. Here it is assumed that demand rate is uncertain in fuzzy sense, that is, it is imprecise in nature and so demand rate is taken as triangular fuzzy number. Then by using -cut for defuzzification the total variable cost per unit time is derived. Therefore the problem is reduced to crisp average costs. The multiobjective model is solved by Global Criteria method with the help of GRG (Generalized Reduced Gradient) Technique. In this model shortages are permitted and fully backordered. Numerical examples are given to illustrate the solution procedure of the two models

The Utilization of Soft Computing in Ordering Cycle Management

Dizertační práce se zabývá možnostmi využití pokročilých metod rozhodování Soft Computingu při řízení objednávkového cyklu podniku. Hlavním cílem dizertační práce je navržení modelu umělé neuronové sítě s optimální architekturou pro řízení objednávkového cyklu podniku v rámci řízení dodavatelského řetězce. Vytvořený model bude sloužit v organizaci působící v oblasti obchodního podnikání pro zajištění plynulého materiálového toku. Součástí dizertační práce je rovněž konstrukce a ověření modelu umělé neuronové sítě pro predikci prodeje a srovnání výsledků a vhodnosti použití s běžnými a dosud používanými statistickými metodami. Dále se dizertační práce zabývá nalezením vhodné architektury umělé neuronové sítě pro stanovení velikosti objednávky na základě zadaných vstupů. Ke zpracování modelu bylo využito metod statistického zpracování dat, ekonomického modelování, Soft Computingu a poznatků ohledně stavu vědeckého poznání řešené problematiky z posledních let.This doctoral thesis deals with possibilities of using advanced methods of decision-making - Soft Computing, in company’s ordering cycle management. The main aim of the thesis is to propose an artificial neural network model with an optimal architecture for ordering cycle management within the supply chain management. The proposed model will be employed in an organization involved in retailing to ensure smooth material flow. A design and verification of artificial neural networks model for sales prediction is also part of this doctoral thesis as well as a comparison of results and usability with standard and commonly used statistical methods. Furthermore, the thesis deals with finding a suitable artificial neural network model with architecture capable of solving the lot-size problem according to specified inputs. Methods of statistical data processing, economical modelling and advanced decision-making (Soft Computing) were utilized during the model designing process.

Pricing and Remanufacturing Decisions of a Decentralized Fuzzy Supply Chain

The optimal pricing and remanufacturing decisions problem of a fuzzy closed-loop supply chain is considered in this paper. Particularly, there is one manufacturer who has incorporated a remanufacturing process for used products into her original production system, so that she can manufacture a new product directly from raw materials or from collected used products. The manufacturer then sells the new product to two different competitive retailers, respectively, and the two competitive retailers are in charge of deciding the rates of the remanufactured products in their consumers’ demand quantity. The fuzziness is associated with the customer’s demands, the remanufacturing and manufacturing costs, and the collecting scaling parameters of the two retailers. The purpose of this paper is to explore how the manufacturer and the two retailers make their own decisions about wholesale price, retail prices, and the remanufacturing rates in the expected value model. Using game theory and fuzzy theory, we examine each firm’s strategy and explore the role of the manufacturer and the two retailers over three different game scenarios. We get some insights into the economic behavior of firms, which can serve as the basis for empirical study in the future

Supply chain inventory control for the iron and steel industry

fi=vertaisarvioitu|en=peerReviewed