The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Manoranjan Maiti - One of the best experts on this subject based on the ideXlab platform.
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a production repairing inventory model with fuzzy rough coefficients under inflation and time Value of Money
Applied Mathematical Modelling, 2013Co-Authors: Madhab Mondal, Amit Kumar Maity, Manas Kumar Maiti, Manoranjan MaitiAbstract:Abstract In this paper, a production-repairing inventory model in fuzzy rough environment is proposed incorporating inflationary effects where a part of the produced defective units are repaired and sold as fresh units. Here, production and repairing rates are assumed as dynamic control variables. Due to complexity of environment, different costs and coefficients are considered as fuzzy rough type and these are reduced to crisp ones using fuzzy rough expectation. Here production cost is production rate dependent, repairing cost is repairing rate dependent and demand of the item is stock-dependent. Goal of the research work is to find decisions for the decision maker (DM) who likes to maximize the total profit from the above system for a finite time horizon. The model is formulated as an optimal control problem and solved using a gradient based non-linear optimization method. Some particular cases of the general model are derived. The results of the models are illustrated with some numerical examples.
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two storage inventory problem with dynamic demand and interval Valued lead time over finite time horizon under inflation and time Value of Money
European Journal of Operational Research, 2008Co-Authors: Shyamal Kumar Mondal, Manoranjan MaitiAbstract:A finite time horizon inventory problem for a deteriorating item having two separate warehouses, one is a own warehouse (OW) of finite dimension and other a rented warehouse (RW), is developed with interval-Valued lead-time under inflation and time Value of Money. Due to different preserving facilities and storage environment, inventory holding cost is considered to be different in different warehouses. The demand rate of item is increasing with time at a decreasing rate. Shortages are allowed in each cycle and backlogged them partially. Shortages may or may not be allowed in the last cycle and under this circumstance, there may be three different types of model. Here it is assumed that the replenishment cycle lengths are of equal length and the stocks of RW are transported to OW in continuous release pattern. For each model, different scenarios are depicted depending upon the re-order point for the next lot. Representing the lead-time by an interval number and using the interval arithmetic, the single objective function for profit is changed to corresponding multi-objective functions. These functions are maximized and solved by Fast and Elitist Multi-objective Genetic Algorithm (FEMGA). The models are illustrated numerically and the results are presented in tabular form.
Ilkyeong Moon - One of the best experts on this subject based on the ideXlab platform.
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the effects of inflation and time Value of Money on an economic order quantity model with a random product life cycle
European Journal of Operational Research, 2000Co-Authors: Ilkyeong MoonAbstract:Abstract For several decades, the Economic Order Quantity (EOQ) model and its variations have received much attention from researchers. Recently, there has been an investigation into an EOQ model incorporating a random product life cycle and the concept of time-Value of Money. This paper extends the previous research in several areas. First, we investigate the impact of inflation on the choice of replenishment quantities. Second, the unit cost, which has been inadvertently omitted in the previous research, is included in the objective function to properly model the problem. Third, we consider the normal distribution as a product life cycle in addition to the exponential distribution. Fourth, we develop a simulation model which can be used for any probability distribution.
K S Chaudhuri - One of the best experts on this subject based on the ideXlab platform.
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an imperfect production process for time varying demand with inflation and time Value of Money an emq model
Expert Systems With Applications, 2011Co-Authors: Biswajit Sarkar, Shib Sankar Sana, K S ChaudhuriAbstract:Abstract The paper deals with an economic manufacturing quantity (EMQ) model for time-dependent (quadratic) demand pattern. Every manufacturing sector wants to produce perfect quality items. But in long run process, there may arise different types of difficulties like labor problem, machinery capabilities problems, etc., due to that the machinery systems shift from in-control state to out-of-control state as a result the manufacturing systems produce imperfect quality items. The imperfect items are reworked at a cost to become the perfect one. The rework cost may be reduced by improvements in product reliability i.e., the production process depend on time and also the reliability parameter. We want to determine the optimal product reliability and production rate that achieves the biggest total integrated profit for an imperfect manufacturing process using Euler–Lagrange theory to build up the necessary and sufficient conditions for optimality of the dynamic variables. Finally, a numerical example is discussed to test the model which is illustrated graphically also.
M Maiti - One of the best experts on this subject based on the ideXlab platform.
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Optimal time-dependent production policy under random time horizon
OPSEARCH, 2019Co-Authors: J. N. Roul, K. Maity, S. Kar, M MaitiAbstract:A production inventory model with linearly time dependent production rate to a certain period and then with constant production rate is developed in random time horizon under inflation and time Value of Money. It is assumed that time period i.e. business period is random and follows exponential distribution with known mean. Demand is linearly stock-dependent. With experience unit production cost decreases with cycles and a part of the set up cost decreases with time. Here also holding and set up costs are imprecise and the optimistic/pessimistic equivalent of fuzzy objective function is obtained by using possibility/necessity measure of fuzzy event. The model is formulated as a cost minimization problem for a production controlled inventory system and solved with the help of GRG (LINGO-14.0) technique(cf. Gabriel and Ragsdell in AMSE J Eng Ind 99:384–00, 1977). The results of the models are obtained for some numerical data and then presented in tabular forms. Some sensitivity analyses are presented for the expected total cost of a model with respect to demand, combined effect of inflation, the time Value of Money and mean Value of time horizon distribution. In real-life the inventory parameters are uncertain. Here in general format, a production controlled inventory model is formulated with imprecise data and made crisp using fuzzy measures in both optimistic and pessimistic senses. It is shown numerically that cost in pessimistic sense is more than that in optimistic sense.
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an inventory model for a deteriorating item with displayed stock dependent demand under fuzzy inflation and time discounting over a random planning horizon
Applied Mathematical Modelling, 2009Co-Authors: Manas Kumar Maiti, M MaitiAbstract:An inventory model for a deteriorating item (seasonal product) with linearly displayed stock dependent demand is developed in imprecise environment (involving both fuzzy and random parameters) under inflation and time Value of Money. It is assumed that time horizon, i.e., period of business is random and follows exponential distribution with a known mean. The resultant effect of inflation and time Value of Money is assumed as fuzzy in nature. The particular case, when resultant effect of inflation and time Value is crisp in nature, is also analyzed. A genetic algorithm (GA) is developed with roulette wheel selection, arithmetic crossover, random mutation. For crisp inflation effect, the total expected profit for the planning horizon is maximized using the above GA to derive optimal inventory decision. On the other hand when inflationary effect is fuzzy then the above expected profit is fuzzy in nature too. Since optimization of fuzzy objective is not well defined, the optimistic/pessimistic return of the expected profit is obtained using possibility/necessity measure of fuzzy event. Fuzzy simulation process is proposed to determine this optimistic/pessimistic return. Finally a fuzzy simulation based GA is developed and is used to maximize the above optimistic/pessimistic return to get optimal decision. The models are illustrated with some numerical examples and some sensitivity analyses have been presented.
Zaid T Balkhi - One of the best experts on this subject based on the ideXlab platform.
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an optimal solution of a general lot size inventory model with deteriorated and imperfect products taking into account inflation and time Value of Money
International Journal of Systems Science, 2004Co-Authors: Zaid T BalkhiAbstract:This paper considers a general production lot size inventory model with deteriorated and imperfect products taking into account inflation and time Value of Money. The production, demand, and deterioration rates are known, continuous, and differentiable functions of time. Shortages are allowed, but only a fraction of the stock out is backordered, and the rest is lost. Under these general assumptions, the inventory model is formulated, and a closed form of the total relevant costs of the underlying inventory system is obtained. Sufficient conditions which lead to a minimal solution of the considered problem are derived. Then, a rigorous mathematical analysis is used to prove that such a minimal solution is unique and global-optimal. A numerical verification of the proposed model is also given.
