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Rakhee Kulshrestha

Bio: Rakhee Kulshrestha is an academic researcher from Birla Institute of Technology and Science. The author has contributed to research in topics: Cognitive radio & Computer science. The author has an hindex of 3, co-authored 10 publications receiving 53 citations.

Papers
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Journal ArticleDOI
TL;DR: A systemic review of perishable inventory models along various dimensions 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.
Abstract: 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.,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.,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.,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.,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.,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.

58 citations

Journal ArticleDOI
TL;DR: This work proposes a model that generalizes some of the previously published ones on working-vacation-breakdown-repair queues and carries out the steady-state analysis, and proves decomposition results for the rate matrix and the mean number in the system under some special cases.

25 citations

Journal ArticleDOI
TL;DR: The transient dynamics from the perspectives of dependability theory in CRNs are investigated using a multi-dimensional continuous time Markov chain (CTMC) and numerical results illustrate the potential of the proposed scheme to achieve major gains in the performance of error-prone CRNs.

7 citations

Journal ArticleDOI
TL;DR: Numerical results are presented which illustrate that the provision of queues under the proposed retrial policy increases overall network resource utilization and throughput while decreasing blocking and dropping probabilities.
Abstract: Cognitive radio is an emerging technology, aimed at efficient use of the scarce radio spectrum. In cognitive radio networks (CRNs), spectrum licensed to the primary users (PUs) is shared by the secondary users (SUs) which affects the performance of the network. This paper proposes a novel spectrum management scheme for CRNs, where heterogeneous secondary real-time and non-real time users compete for the available channels with primary users and utilize two types of buffers under the probability retrial policy. To enhance the quality of service (QoS) for the secondary users (SUs), spectrum handoff and call buffering strategies with retrial policy are employed jointly so that SUs that would otherwise be blocked or forcibly dropped could be queued and possibly served later. The whole system is modeled using a multi-dimensional continuous-time Markov chain (CTMC) and accordingly, the QoS performance metrics are derived. Numerical results are presented which illustrate that the provision of queues under the proposed retrial policy increases overall network resource utilization and throughput while decreasing blocking and dropping probabilities.

4 citations

DOI
TL;DR: A clear guideline on the selection of forecasting models based on the desired time horizon is provided on the analysis and forecasting of GHI data at two different locations in India, namely Pokhran and Bitta.

3 citations


Cited by
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Journal ArticleDOI
TL;DR: The obtained results show that applying VMI policy on two-echelon supply chain for perishable products is an effective approach to optimize the profitability of the proposed network.

54 citations

Journal ArticleDOI
TL;DR: An integrated Shannon’s entropy multi-criteria decision making method is used for the evaluation and assessment of conventional and renewable energy sources for sustainable development of energy sector in India and solar energy was shown to be particularly well suited for India.

53 citations

Posted Content
TL;DR: The impact of perishability and cost parameters on the performance of the can-order policy and compare it to the optimal periodic review (s,S) policy are investigated.
Abstract: This paper considers the continuous review can-order ðs; c; SÞ policy for coordinating the replenishment of multiple perishable items with random lifetimes. For zero lead time, we model this inventory system as a Markov process. An iterative procedure is proposed to solve the joint replenishment problem for perishable items under positive lead time. We investigate the impact of perishability and cost parameters on the performance of the can-order policy and compare it to the optimal periodic review (s,S) policy.

27 citations

Posted Content
TL;DR: In this article, an order up to level (T, S) policy for perishable items with random lifetime is considered and the model is modeled as a Markov process in which stationary regime can be characterised.
Abstract: We consider an order up to level (T, S) policy for perishable items with random lifetime. We investigate two cases: the first one is the case where excess demand is completely lost and the second one deals with full backorders. Demands arrive according to a Poisson process. The lifetime of each item is assumed to be exponentially distributed and the procurement lead time is constant. We also assume that there is at most one outstanding order at any time. We model this inventory system as a Markov process in which stationary regime can be characterised. This model allows us to get insights on the impact of the model parameters on the overall system performance in terms of costs. Keywords: perishable items; periodic review inventory control; Markov process 1. Introduction Perishable items are one of the most important sources of revenue in grocery industry and food stuff (Deniz 2007). They are also an important source of waste due to their limited lifetime. Lystad, Ferguson, and Alexopoulos (2006) report that about $30 billion are lost due to perishable products in US grocery industry. Consequently, the effect of perishability cannot be disregarded. A large part of investigations analysing perishable inventory systems in the literature assume that the inventory is reviewed continuously and products have stochastic lifetime. However, periodic inventory control policies are used in many practical situations, especially in the case of multi-item, multi-echelon inventory systems, where items are often ordered within a common frequency. For instance, van Donselaar et al. (2010) report that stores that order through an automated store ordering system receive at most one shipment per day from the central warehouse which regroups all the items to be delivered that day. The literature concerning perishable inventory systems can be classified depending on whether the inventory is controlled continuously or periodically and whether products' lifetime is assumed to be constant or stochastic. In almost all models, the FIFO issuing policy is used. Other types of issuing policies exist such as the LIFO issuing policy used by Cohen and Prastacos (1978), and the disposal decision model studied by Martin (1986). Since the present paper does not consider the case of a continuous review inventory system, we refer the reader to Kouki (2010), Karaesmen, Scheller-Wolf, and Deniz (2011) and Nahmias (2011) that deal with such specific inventory policies. For periodic review perishable inventory systems with deterministic lifetime, the problem of finding optimal ordering policy is well known as the fixed-life perishability problem (FLPP) (Nandakumar and Morton 1993). If products cannot be held in stock more than one period, the FLPP is reduced to the known Newsboy problem (Khouja 1999). Van Zyl (1964) proposes a first dynamic programme approach for products having a lifetime of two periods and derives the optimal policy when shortage costs are charged to unsatisfied demand. Nahmias and Pierskalla (1973) build a model where they charge a cost associated with the outdating (perished items) and show that the order quantity for a perishable item is always smaller than the one of a non-perishable item. This work is extended by Fries (1975) and Nahmias (1975) to the case where products have three or more units of lifetime. Nahmias (1975) assumes that the cost of outdating is charged to the period in which the order arrives while Fries (1975) assumes that this cost is charged at the period where outdating occurs. These two models are shown to be identical by Nahmias (1977) when the remaining number of periods in the horizon exceeds the product lifetime. Then, Nahmias (1978) considers a fixed ordering cost and emphasises the difficulty to compute the optimal policy by a multidimensional dynamic programming approach. This arises since the dynamic programming approach needs to track the different ages' categories of items in stock. However, direct computation of an optimal policy turns out to be impractical because of the dimension of the dynamic programme generated by the different age categories. Therefore, several other researches have focused on developing heuristic approximations. Nahmias (1976) considers only two ages: the total old quantity of on-hand inventory

27 citations

Journal ArticleDOI
Chen Wei1, Wen-Wen Gao1, Zhi-Hua Hu1, Yu-Qi Yin1, Shi-De Pan1 
TL;DR: The examined cold chain distribution problem is an extension of inventory routing problems (IRPs) while the combination of SOVs and OSVs with different route time limits makes the present solution methods inapplicable.

25 citations