A multi-server perishable inventory system with negative customer

Yadavalli, Venkata S. Sarma; Arivarignan, G.; Adetunji, Olufemi

doi:10.1016/j.cie.2010.07.032

Cited by 26 publications

(12 citation statements)

References 17 publications

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“…If environmental factors such as economic and marketing conditions change during the product life and have a significant effect on the demand, then the assumption that the demand in each period is a random variable and is independent of environmental factors apart from time will be incorrect. In such real life situations, the Markov chain approach provides a flexible alternative for modeling the demand process [55,276,321,335,336,[339][340][341][343][344][345][346]; not only does it significantly generalize the Poisson process [55,272,278,280,281,287,290,297,303,304,307,308,316,333,338,341], but it is also a convenient tool for modeling both the renewal and non-renewal demand arrivals. However, despite this fact, the Markovian assumption holds for demand processes with relatively low variation coefficients, i.e., in cases where high demand variances are observed, the non-stationary assumption does not hold in the Markovian environment because standard periods of constant length may introduce memory and generate correlated demand distributions within periods.…”

Section: Classification According To the Demand And Deteriorationmentioning

confidence: 99%

Inventory models for managing deteriorating products: a literature review

Pérez¹,

Torres²

2020

Preprint

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The problem of determining the economic order quantity has long attracted the attention of researchers, and several models have been developed to meet requirements under different circumstances at minimum cost. In the present paper, we conduct a structural content analysis of 317 selected peer-reviewed research articles that were published during the period 2001-2018 and ranked with a quartile score of Q1 by either ISI or Scopus database. By discussing the main topics of the inventory modeling literature, we provide a comprehensive view of the past research dealing with the management of deteriorating items. Here, we focus on items undergoing physical modification during the planning period, which encompasses a wide variety of products such as fresh produce, processed food, pharmaceuticals and blood products. Therefore, based on our holistic analysis, we identify new trends and we highlights crucial research opportunities to develop more comprehensive and practical models.

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Section: Classification According To the Demand And Deteriorationmentioning

confidence: 99%

Inventory models for managing deteriorating products: a literature review

Pérez¹,

Torres²

2020

Preprint

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“…According to Gürler and Özkaya (2008), demand arrival followed renewal process with random batch sizes. There can be cases when items required processing (Cai et al , 2010; Yadavalli et al , 2011), then the expected waiting time and queue length also take into consideration in addition to the holding time to evaluate the performance of the system which will be useful to implement inventory control policies. In fact, with the growing uncertainty in the modern business environment, the assumption of deterministic demand is far from truth, so stochastic demand has attracted more and more attentions.…”

Section: Classification Of Perishable Inventory Modelsmentioning

confidence: 99%

State-of-the-art literature review on inventory models for perishable products

Chaudhary

Kulshrestha

Routroy

2018

JAMR

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Purpose The purpose of this paper is to review and analyze the perishable inventory models along various dimensions such as its evolution, scope, demand, shelf life, replenishment policy, modeling techniques and research gaps. Design/methodology/approach In total, 418 relevant and scholarly articles of various researchers and practitioners during 1990-2016 were reviewed. They were critically analyzed along author profile, nature of perishability, research contributions of different countries, publication along time, research methodologies adopted, etc. to draw fruitful conclusions. The future research for perishable inventory modeling was also discussed and suggested. Findings There are plethora of perishable inventory studies with divergent objectives and scope. Besides demand and perishable rate in perishable inventory models, other factors such as price discount, allow shortage or not, inflation, time value of money and so on were found to be combined to make it more realistic. The modeling of inventory systems with two or more perishable items is limited. The multi-echelon inventory with centralized decision and information sharing is acquiring lot of importance because of supply chain integration in the competitive market. Research limitations/implications Only peer-reviewed journals and conference papers were analyzed, whereas the manuals, reports, white papers and blood-related articles were excluded. Clustering of literature revealed that future studies should focus on stochastic modeling. Practical implications Stress had been laid to identify future research gaps that will help in developing realistic models. The present work will form a guideline to choose the appropriate methodology(s) and mathematical technique(s) in different situations with perishable inventory. Originality/value The current review analyzed 419 research papers available in the literature on perishable inventory modeling to summarize its current status and identify its potential future directions. Also the future research gaps were uncovered. This systemic review is strongly felt to fill the gap in the perishable inventory literature and help in formulating effective strategies to design of an effective and efficient inventory management system for perishable items.

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“…Now exploiting max-min operator, which was first developed by Bellman and Zadeh [28] long back and subsequently used by Zimmermann [32], etc. the solution of the FNLPP (12) can be obtained from Max a subject to For the proposed fuzzy model given by (11), we define the membership function of fuzzy inventory minimum cost and fuzzy deteriorationrate as follows :…”

Section: Fuzzy Modelmentioning

confidence: 99%

“…To find the extreme order quantity, which minimizes the total fuzzy cost function. Fuzzy cost function is derived with the help of Zimmerman [32] and its solution is obtained with the help of Kaufmann and Gupta [33]. In section 2, assumptions and notations of the proposed model are listed.…”

Section: Introductionmentioning

confidence: 99%

An inventory model with fuzzy deterioration and fully backlogged shortage under inflation

Shabani

Mirzazadeh

Sharifi

2014

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Looking through the inventory models with deteriorating items shows that the deterioration rate is considered constant in most of the previous researches. But,in the real world, deterioration rate is not actually constant and slightly disturbed from its original crisp value. In this paper a more realistic inventory model with fuzzy deterioration and fully backlogged shortage under inflation is considered. The mathematical model is formulated to obtain the optimal value of the fuzzy total cost. The numerical example is used to illustrate the computation procedure. A sensitivity analysis is also carried out to get the sensitiveness of the tolerance of different input parameters.

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A multi-server perishable inventory system with negative customer

Cited by 26 publications

References 17 publications

Inventory models for managing deteriorating products: a literature review

Inventory models for managing deteriorating products: a literature review

State-of-the-art literature review on inventory models for perishable products

An inventory model with fuzzy deterioration and fully backlogged shortage under inflation

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