Multi-item inventory models with price dependent demand under flexibility and reliability consideration and imprecise space constraint: A geometric programming approach

Panda, Debdulal; Maiti, Manoranjan

doi:10.1016/j.mcm.2008.10.019

Cited by 39 publications

(8 citation statements)

References 32 publications

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“…Applied structures for the power functions in current article were used by many researchers with a little difference (Sadjadi et al 2005(Sadjadi et al , 2010(Sadjadi et al , 2012Lee and Kim 1993;Jung and Klein 2001;Leung 2007;Panda and Maiti 2009).…”

Section: ð1þmentioning

confidence: 99%

Joint pricing and production management: a geometric programming approach with consideration of cubic production cost function

et al. 2014

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Coordination and harmony between different departments of a company can be an important factor in achieving competitive advantage if the company corrects alignment between strategies of different departments. This paper presents an integrated decision model based on recent advances of geometric programming technique. The demand of a product considers as a power function of factors such as product's price, marketing expenditures, and consumer service expenditures. Furthermore, production cost considers as a cubic power function of outputs. The model will be solved by recent advances in convex optimization tools. Finally, the solution procedure is illustrated by numerical example.

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Section: ð1þmentioning

confidence: 99%

Joint pricing and production management: a geometric programming approach with consideration of cubic production cost function

et al. 2014

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“…The model is formulated to maximize the expected average profit. Panda and Maiti (2009) proposed a multi-item economic production quantity (EPQ) models considering selling price dependent demand, infinite production rate, stock dependent unit production and holding costs. Flexibility and reliability consideration are introduced in the production process.…”

Section: Reliability Adjusted Epq (Economic Production Quantity) Modelmentioning

confidence: 99%

A literature review on inventory modeling with reliability consideration

Ahmed

Sultana²

2013

10.5267/j.ijiec

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Inventories are the materials stored either waiting for processing or experiencing processing and in some cases for future delivery. Inventories are treated both as blessings and evil. As they are like money placed in a drawer, assets tied up in investments, incurring costs for the care of the stored material and also subject to spoilage and obsolescence there have been a spate of programs developed by industries, all aimed at reducing inventory levels and increasing efficiency on the shop floor. Nevertheless, they do have positive purposes such as stable source of input required for production, less replenishment and may reduce ordering costs because of economies of scale. Finished goods inventories provide for better customer service. So formulating a suitable inventory model is one of the major concerns for an industry. Again considering reliability of any process is an important trend in the current research activities. Inventory models could be both deterministic and probabilistic and both of which must account for the reliability of the associated production process. This paper discusses the major works in the field of inventory modeling driven by reliability considerations, which ranges from the very beginning to latest works just published.

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“…Reliability deals with reducing failures over a time interval and is a measure of the odds for failure free operation during a given interval, improving reliability occurs at an increase development cost. Mettas (2000) developed reliability allocation and optimization for complex systems and later by several researchers such as Panda et al (2008), Panda and Maiti (2009), Sarkar (2012), Maity (2014a) and others.…”

Section: Introductionmentioning

confidence: 99%

Several Intelligent Techniques to Solve Various Warehouse Problems in Uncertain Environment

Maity¹

2015

Intelligent Techniques in Engineering Management

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In this chapter, several intelligent techniques to solve several warehouse problems have discussed in uncertain environment. In first model, analogous to chance constraints, real-life necessary and possibility constraints in the context of two warehouses multi-item dynamic production-inventory control system with imprecise holding and production costs are defined and defuzified following fuzzy relations. Hence, a realistic two warehouse multi-item production-inventory model without shortages and fuzzy constraints has been formulated and solved for optimal production with the objective of having maximum profit. Here, the rate of production is assumed to be a function of time and considered as a control variable. Also the present system produces some defective units alongwith the perfect ones and the rate of produced defective units is stochastic in nature. Here demand of the units is stock dependent and known and the defective units are selling with reduced prices. The space required per unit item, available storage space are assumed to be imprecise. The budget constraints is also imprecise. The space and budget constraints are of necessity and/or possibility types. The model is reduced to an equivalent deterministic model using necessary and possibility constrained and solved for optimum production function using Pontryagin's Optimal Control policy, the Kuhn-Tucker conditions and mathematica software 9.0. The engineering students in Optimization engineering and M.B.A.s in the business curriculum can used the model easily. In second model, a three layer supply chain production inventory model (TLSCPIM) under conditionally permissible delay in payments is formulated in fuzzy-rough and Liu uncertain environment. Supplier's supply the item at a finite rate. Manufacturer has also purchased the said item from supplier and produced the item in a certain rate which is the decision variable. Manufacturer sale his product to the retailer and also give the delay in payment to the retailer. Retailer purchase the item from manufacture and to sale the customers. Ideal costs of supplier, manufacturer and retailer have been taken into account. Also using expectation of fuzzy rough number and Liu uncertain number, the fuzzy rough

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Multi-item inventory models with price dependent demand under flexibility and reliability consideration and imprecise space constraint: A geometric programming approach

Cited by 39 publications

References 32 publications

Joint pricing and production management: a geometric programming approach with consideration of cubic production cost function

Joint pricing and production management: a geometric programming approach with consideration of cubic production cost function

A literature review on inventory modeling with reliability consideration

Several Intelligent Techniques to Solve Various Warehouse Problems in Uncertain Environment

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