Optimization of EOQ Model with Limited Storage Capacity by Neutrosophic Geometric Programming (original) (raw)
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In this paper, a fuzzy economic order quantity (E.O.Q) model with shortages under fully backlogging and constant demand is formulated and solved. Here the model is solved by fuzzy signomial geometric programming (FSGP) technique. Fuzzy signomial geometric programming (FSGP) technique provides a powerful technique for solving many non-linear problems. Here we have proposed a new idea that is fuzzy modified signomial geometric programming (FMSGP) and some necessary theorems have been derived. Finally, these are illustrated by some numerical examples and applications.
Zenodo (CERN European Organization for Nuclear Research), 2022
In the competitive market, a customer's choice for an item depends on several factors like management's marketing strategy and service, the item's price and greenness. Demand increases with the marketing strategy, service and item's greenness, but it is inversely related to the item's price. These relations are non-linear and imprecise. Recently, neutrosophic set has been introduced to represent impreciseness more realistically. Moreover, resources (capital, storage space, etc.) are generally uncertain (random or imprecise). Considering the above business scenarios, profit maximization EOQ models with price, marketing, service, and green dependent neutrosophic demand and order quantity dependent unit production cost are developed under different uncertain resource constraints. Models' parameters are pentagonal neutrosophic (PN) numbers. The proposed models are first made deterministic and then solved using the geometric programming technique. The PN parameters are made crisp using the score function. The random, fuzzy, rough and trapezoidal neutrosophic resource constraints in different models are converted to crisp using possibility measure, chance-constrained technique, trust measure and (α, β, γ)-cut with weighted mean, respectively. These processes reduce the objective function and constraints to signomial forms, and the reduced problems are solved by geometric programming technique with the degree of difficulty 2. Numerical experiments and sensitivity analyses are performed to illustrate the models.
Zenodo (CERN European Organization for Nuclear Research), 2021
We have considered a deterministic inventory model with time-dependent demand and holding cost and time varying deterioration where shortages are allowed and partially backlogged. To reduce deterioration we have considered here a preservation condition. In the presence uncertainty we have taken cost parameters as generalized trapezoidal fuzzy number. The proposed model has been solved by neutrosophic hesitant fuzzy programming approach, fuzzy nonlinear programming approach and fuzzy additive goal programming technique. The model is illustrated with numerical example and we presented sensitivity analysis finally.
Fuzzy decision-making approach in geometric programming for a single item EOQ model
2015
Background and methods : Fuzzy decision-making approach is allowed in geometric programming for a single item EOQ model with dynamic ordering cost and demand-dependent unit cost. The setup cost vari es with the quantity produced/purchased and the modification of objective function with storage area in the presen ce of imprecisely estimated parameters are investigated. It incorpor ates all concepts of a fuzzy arithmetic approach, t he quantity ordered, and demand per unit compares both fuzzy geometric programming technique and other models for linear membership functions. Results and conclusions : Investigation of the properties of an optimal solu tion allows developing an algorithm whose validity is illustrated through an example problem and the results discussed. Sensitivity analysis of the optimal solution is also studied with respect to changes in different p arameter values.
A note on fuzzy inventory model with storage space and budget constraints
Applied Mathematical Modelling, 2009
In 1997, Roy and Maiti developed a fuzzy EOQ model with fuzzy budget and storage capacity constraints where demand is influenced by the unit price and the setup cost varies with the quantity purchased [T.K. Roy, M. Maiti, A fuzzy EOQ model with demand-dependent unit cost under limited storage capacity, Eur. J. Oper. Res. 99 ]. However, their procedure has some questionable points and their numerical examples contain rather peculiar results. The purpose of this paper is threefold. First, for the same inventory model with fuzzy constraints, based on the max-min operator, we proposed an improved solution procedure. Second, we review the solution procedure by Roy and Maiti that is based on Kuhn-Tucker approach to point out their questionable results. Third, we compare Roy and Maiti's approach with ours to explain why our approach can solve the problem and theirs cannot. Numerical examples provided by them also support our findings.
International Journal of Mathematics in Operational Research, 2011
A multi-item EPQ model for deteriorating items is built-up with limited storage space and with flexibility and reliability of production process. Here, production rate for the items is depends on the demand and items deteriorate at constant rates. Due to high rent in market place, storage space is considered limited and imprecise in nature. Inventory related costs, storage space and other parameters are imprecise and taken as it triangular fuzzy number. We solve this inventory decision problem using Modified Geometric Programming (MGP) method. Following the theoretical treatment, we provide a numerical example to demonstrate that MGP has potential as a valuable analytical tool for researchers. At the end some sensitivity analysis with different parameters are made.
A Single Item Non Linear Programming (NLP) Economic Order Quantity Model with Space Constraint
Tij S Research Journal of Social Science Management Rjssm, 2013
This paper considers a single item non linear inventory problem with storage constraint where the demand of the items is constant. A Single item economic order quantity (EOQ) model is a stylized model using crisp arithmetic approach in decision making process with demand unit cost and dynamic ordering cost varies with the quantity produced/Purchased under two constraints. This paper considers the modification of objective function, limited storage area in the presence of estimated parameters. Due to increasingly market competition, space has become the biggest expense in company's inventory expenditure and has frequently used as the most effective weapon by a lot of companies to reduce their costs in the short term. In this paper the concept of the Non-linear Programming technique is applied to solve a single item inventory problem with storage constraint. The solution is illustrated by numerical example and the results of different models are compared and investigation of the properties of an optimal solution allows developing an algorithm for obtaining solution through LINGO 13.0 version. Furthermore, sensitivity analysis of the optimal solution is studied with respect to changes in different parameter values and to draw managerial insights of proposed model over an infinite planning horizon.