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    <title>DSpace Collection:</title>
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    <dc:date>2026-04-05T17:19:54Z</dc:date>
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    <title>Pricing strategy of competing retailers in a two layer supply chain under nonlinear stochastic demand</title>
    <link>http://localhost:80/xmlui/handle/123456789/7407</link>
    <description>Title: Pricing strategy of competing retailers in a two layer supply chain under nonlinear stochastic demand
Authors: Chakraborty, Dipankar
Abstract: This paper develops mechanisms to deal the strategic issue that arises in a two-echelon closed-loop supply chain comprising of one manufacturer and two competing retailers. The chain works under stochastic nonlinear demand. Here the manufacturer works as the supplier and the retailers compete with each other on the basis of their retail price. The prime objective is to investigate a news-vendor model to govern the optimal order quantity. A buyback contract between the manufacturer and retailer has been considered and scenario of shortage has also been contemplated. The profit functions of manufacturer and two retailers are analysed following centralised approach. A numerical example is given to illustrate the theoretical results. Computational results show that it is always beneficial in integrated system for the members of the chain.</description>
    <dc:date>2022-01-01T00:00:00Z</dc:date>
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  <item rdf:about="http://localhost:80/xmlui/handle/123456789/7406">
    <title>Discussion on Stability and Hopf-bifurcation of an Infected Prey under Refuge and Predator</title>
    <link>http://localhost:80/xmlui/handle/123456789/7406</link>
    <description>Title: Discussion on Stability and Hopf-bifurcation of an Infected Prey under Refuge and Predator
Authors: Sarkar, Moulipriya; Das, Tapasi
Abstract: The paper deals with the case of non-selective predation in a partially infected prey-predator system, where both the susceptible prey and predator follow the law of logistic growth and some preys avoid predation by hiding. The disease-free preys get infected in due course of time by a certain rate. However, the carrying capacity of the predator population is considered proportional to the sum-total of the susceptible and infected prey. The positivity and boundedness of the solutions of the system are studied and the existence of the equilibrium points and stability of the system are analyzed at these points. The effect of the infected prey-refuge on each population density is also discussed. It is observed that a Hopf-bifurcation may occur about the interior equilibrium, where the refuge parameter is considered as the bifurcation parameter. The analytical findings are illustrated through computer simulation using Maple that show the reliability of the model from the&#xD;
ecological point of view.</description>
    <dc:date>2021-01-01T00:00:00Z</dc:date>
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  <item rdf:about="http://localhost:80/xmlui/handle/123456789/7405">
    <title>A multi-warehouse partial backlogging inventory model for deteriorating items under inflation when a delay in payment is permissible</title>
    <link>http://localhost:80/xmlui/handle/123456789/7405</link>
    <description>Title: A multi-warehouse partial backlogging inventory model for deteriorating items under inflation when a delay in payment is permissible
Authors: Das, Debasis; Roy, Arindam; Kar, Samarjit
Abstract: In this paper we develop a multi-item multi-warehouse inventory model for dete-riorating items for m secondary warehouses (SWs) and one primary warehouse (PW) withdisplayed stock and price dependent demand under permissible delay in payment. Items aresold from PW which is located at the main market and due to large stock and insufficient spaceof existing PW, excess items are stored at m SWs of finite capacity. Due to different preserv-ing facilities and storage environment, inventory holding cost is considered to be different indifferent warehouses. Here the demand of items is a deterministic function of correspondingselling price and the displayed inventory. Shortages are allowed and partially backlogged.The items of SWs are transported to the PW in continuous release pattern and associatedtransportation cost is proportional to the distance from PW to SWs. Here Mi (&lt; Ti , cycletime) be the period of permissible delay in settling account for ith item, without the interestcharges. But if the retailer settles the account after Mi , he will have to pay with interest percycle for the inventory not sold after the due date Mi . A single objective inventory problemis solved numerically by developing Genetic algorithm and the maximum average profit andthe corresponding optimum decision variables are evaluated. Finally the model is illustratedusing a numerical example. A sensitivity analysis of the optimal solution with respect to theparameters of the system is carried out.
Description: DOI 10.1007/s10479-014-1691-6</description>
    <dc:date>2020-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://localhost:80/xmlui/handle/123456789/7404">
    <title>Fully fuzzy inventory model with price-dependent demand and time varying holding cost under fuzzy decision variables</title>
    <link>http://localhost:80/xmlui/handle/123456789/7404</link>
    <description>Title: Fully fuzzy inventory model with price-dependent demand and time varying holding cost under fuzzy decision variables
Authors: Chakraborty, Dipankar
Abstract: In this paper, we have considered an EOQ inventory model with a price-dependent demand and time varying holding cost in fuzzy environments by employing trapezoidal fuzzy numbers. A fully-fuzzy inventory model is developed where the input parameters and decision variables are fuzzified. For this fuzzy model, an expected value method of defuzzification is employed to find the estimate of the profit function in the fuzzy sense. In addition, a rigorous methodology is constructed to examined for the optimal solution of fully-fuzzy inventory model. The optimal policy for the developed model is determined using the proposed algorithm after defuzzification of the profit function. Finally, a numerical example is provided in order to determine the sensitiveness in the decision variables with respect to fuzziness in the components.
Description: DOI: 10.3233/JIFS-18379</description>
    <dc:date>2019-04-01T00:00:00Z</dc:date>
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