Relevant bibliographies by topics / Joint replenishment problem (JRP)

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  2. Dissertations / Theses
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Academic literature on the topic 'Joint replenishment problem (JRP)'

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Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Joint replenishment problem (JRP)"

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NONNER, TIM, and ALEXANDER SOUZA. "APPROXIMATING THE JOINT REPLENISHMENT PROBLEM WITH DEADLINES." Discrete Mathematics, Algorithms and Applications 01, no. 02 (2009): 153–73. http://dx.doi.org/10.1142/s1793830909000130.

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The objective of the classical Joint Replenishment Problem (JRP) is to minimize ordering costs by combining orders in two stages, first at some retailers, and then at a warehouse. These orders are needed to satisfy demands that appear over time at the retailers. We investigate the natural special case that each demand has a deadline until when it needs to be satisfied. For this case, we present a randomized 5/3-approximation algorithm. We moreover prove that JRP with deadlines is APX-hard. Finally, we extend the known hardness results by showing that JRP with linear delay cost functions is NP-
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LI, CHENGYAN, XIAOFEI XU, and DECHEN ZHAN. "SOLVING JOINT REPLENISHMENT PROBLEM WITH DETERIORATING ITEMS USING GENETIC ALGORITHM." Journal of Advanced Manufacturing Systems 08, no. 01 (2009): 47–56. http://dx.doi.org/10.1142/s0219686709001626.

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Deterioration occurs for most items in the real world, such as decay, spoilage, evaporation, and so on. The deterioration of item may cause extra costs for inventory storage and additional costs from shortage. In this paper, Joint replenishment problem (JRP) model with exponentially distribution deterioration rate was proposed. The objective function of the JRP model was to minimize the setup costs, inventory holding costs and deterioration costs. Genetic algorithm (GA) was used for solving this problem and researches were also made in aspects such as chromosome coding, fitness function, selec
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Ho, Wen-Tsung. "Determining the Optimum Ordering Policy in Multi-Item Joint Replenishment Problem Using a Novel Method." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/469794.

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This work investigates the joint replenishment problem (JRP) involving multiple items where economies exist for replenishing several items simultaneously. The demand rate for each item is known and constant. Shortages are not permitted and lead times are negligible. Many heuristic algorithms have been proposed to find quality solutions for the JRP. In this paper, cycle time division and recursive tightening methods are developed to calculate an efficient and optimal replenishment policy for JRP. Two theorems are demonstrated to guarantee that an optimal solution to the problem can be derived u
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Zapata-Cortes, Julian Andres, Martín Dario Arango-Serna, and Conrado Augusto Serna-Uran. "Application of the joint replenishment problem in a collaborative Inventory approach to define resupply plans in urban goods distribution contexts." DYNA 85, no. 207 (2018): 174–82. http://dx.doi.org/10.15446/dyna.v85n207.72546.

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This article presents an application of the joint replenishment problem (JRP) as the basis for proposing a collaborative inventory model with joint orders, in which multiple customers share the required information to define their supply plans. This information is consolidated by the supplier and it is responsible for carrying out the collaborative joint replenishment process. The application of the model allows generating a replenishment process that reduces costs compared to carrying out the individual plans for each customers and also generates a reduction in the number of trips required, w
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Amaya, Ciro Alberto, Jimmy Carvajal, and Fabian Castaño. "A heuristic framework based on linear programming to solve the constrained joint replenishment problem (C-JRP)." International Journal of Production Economics 144, no. 1 (2013): 243–47. http://dx.doi.org/10.1016/j.ijpe.2013.02.008.

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Wang, Lin, Hui Qu, Yanhui Li, and Jing He. "Modeling and Optimization of Stochastic Joint Replenishment and Delivery Scheduling Problem with Uncertain Costs." Discrete Dynamics in Nature and Society 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/657465.

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The stochastic joint replenishment and delivery scheduling (JRD) problem is a key issue in supply chain management and is a major concern for companies. So far, all of the work on stochastic JRDs is under explicit environment. However, the decision makers often have to face vague operational conditions. We develop a practical JRD model with stochastic demand under fuzzy backlogging cost, fuzzy minor ordering cost, and fuzzy inventory holding cost. The problem is to determine procedures for inventory management and vehicle routing simultaneously so that the warehouse may satisfy demand at a min
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Wang, Lin, Hui Qu, Shan Liu, and Cai-xia Dun. "Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment." Scientific World Journal 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/916057.

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As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse andn-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach co
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Zeng, Yu-Rong, Lin Wang, Xian-Hao Xu, and Qing-Liang Fu. "Optimizing the Joint Replenishment and Delivery Scheduling Problem under Fuzzy Environment Using Inverse Weight Fuzzy Nonlinear Programming Method." Abstract and Applied Analysis 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/904240.

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In reality, decision-makers are always in front of imprecise and vague operational conditions. We propose a practical multiobjective joint replenishment and delivery scheduling (JRD) model with deterministic demand and fuzzy cost. This model minimizes the total cost defuzzified by the signed distance method and maximizes the credibility that the total cost does not exceed the budget level. Then, an inverse weight fuzzy nonlinear programming (IWFNLP) method is adopted to formulate the proposed model. This method embeds the idea of inverse weights into the Max-Min fuzzy model. Thirdly, the fuzzy
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Cheung, Maurice, Adam N. Elmachtoub, Retsef Levi, and David B. Shmoys. "The submodular joint replenishment problem." Mathematical Programming 158, no. 1-2 (2015): 207–33. http://dx.doi.org/10.1007/s10107-015-0920-3.

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Federgruen, Awi, and Yu-Sheng Zheng. "The Joint Replenishment Problem with General Joint Cost Structures." Operations Research 40, no. 2 (1992): 384–403. http://dx.doi.org/10.1287/opre.40.2.384.

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Dissertations / Theses on the topic "Joint replenishment problem (JRP)"

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Rahmouni, Mouna. "Optimisation combinée des approvisionnements et du transport dans une chaine logistique." Thesis, Aix-Marseille, 2015. http://www.theses.fr/2015AIXM4329.

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Le problème d’approvisionnement conjoint (JDP) proposé est un problème de planification des tournées de livraisons sur un horizon de temps décomposé en périodes élémentaires, l’horizon de temps étant la période commune de livraison de tous les produits,. La donnée de ces paramètres permet d’obtenir une formulation linéaire du problème, avec des variables de décision binaires. Le modèle intègre aussi des contraintes de satisfaction de la demande à partir des stocks et des quantités livrées, des contraintes sur les capacités de stockage et de transport.Afin de résoudre aussi le problème de choix
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Canlas, Michael T. Jang Wooseung. "A practical approach to the cyclic multi-bin joint replenishment problem." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6573.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on October 21, 2009). Thesis advisor: Dr. W. Jang. Includes bibliographical references.
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Narayanan, Arunachalam. "Improved formulations, heuristics and metaheuristics for the dynamic demand coordinated lot-sizing problem." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1802.

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Telha, Cornejo Claudio (Claudio A. ). "Algorithms and hardness results for the jump number problem, the joint replenishment problem, and the optimal clustering of frequency-constrained maintenance jobs." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/70446.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 107-110).<br>In the first part of this thesis we present a new, geometric interpretation of the jump number problem on 2-dimensional 2-colorable (2D2C) partial order. We show that the jump number of a 2D2C poset is equivalent to the maximum cardinality of an independent set in a properly defined collection of rectangles in the plane. We then model the geometric problem as a linear program. Even
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Balcik, Burcu. "Multi Item Integrated Location/inventory Problem." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/4/1093640/index.pdf.

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In this study, the design of a three-level distribution system is considered in which a single supplier ships a number of items to the retailers via a set of distribution centers (DC) and stochastic demand is observed at the retailers. The problem is to specify the number and location of the DCs, and the assignment of the retailers to the DCs in such a way that total facility, transportation, safety stock, and joint ordering and average inventory costs are minimized, and customer service requirements are satisfied. Single source constraints are imposed on the assignment of the retailers to the
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Jhe-Yi, Jiang, and 江哲儀. "Solving and Analysis of Joint Replenishment Problem." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/04241539051932475377.

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碩士<br>國立雲林科技大學<br>工業工程與管理研究所碩士班<br>100<br>Joint replenishment problem has been proposed for 40 years. S.K. Goyal tried to get global optimal solution by local optimal. RAND found the relations between global optimal frequency and K_i. This research proposed another heuristic method for the JRP. This heuristic method directly gets the best K_i under the total cost without the association with frequency. Because RAND has best ability in solving JRP, it is a standard solution in this research. This research analyses the heuristic method proposed in this research, S.K. Goyal（1974）and E.A.Silver（19
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Chen, Chun-chin, and 陳鈞智. "The Joint Replenishment Problem of Perishable Commodity." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/99286977846553181252.

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碩士<br>雲林科技大學<br>工業工程與管理研究所碩士班<br>96<br>In order to reduce total inventory costs, an enterprise can use consolidation to save transportation cost and order process cost when it requires multiple products. The consolidation of order multiple products is also called “The Joint Replenishment Problem (JRP)”. The JRP model assumes the planning horizon is infinite. However, many products’ life time is finite in reality. If the inventory replenishment is planned according to this assumption, it will cause some inventories can’t be sold before their expired dates. In order to solve this problem, the st
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Lee, Yi-Chieh, and 李依潔. "The Joint Replenishment Problem Considering Container Transportation Cost." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/66184325211724899163.

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碩士<br>國立交通大學<br>運輸科技與管理學系<br>99<br>Researchers are interested in studying the joint replenishment Problem due to its applications in the globalization of markets and products diversification. Also, the practitioners are motivated to reduce the total costs by replenishing products jointly. The costs in the traditional Joint Replenishment Problem are composed of three parts：(1) major setup cost, (2) minor setup cost and (3) inventory holding cost. This study focused on additionally taking into account the transportation cost subject to using a fixed basic period for the planning of replenishment
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Yeh, Su-Wei, and 葉書瑋. "Integrated Routing Cost With The Joint Replenishment Problem." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/80331854308356347081.

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碩士<br>國立雲林科技大學<br>工業工程與管理研究所碩士班<br>100<br>Traditional joint replenishment problem is based on a second-order supply chain, which is for the multiple retailers and a suppliers common replenishment. In the past, joint replenishment problem and transport routing problem have always been the separate problems but in fact these two problems are inseparable. Thus the research we have here is trying to combine two different NP-hard problem which is ‘Joint Replenishment Problem，JRP’ and ‘traveling salesman problem，TSP’ each accordingly. The result comes out with us using Goyal’s systematic concept of
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Yeh, Che-Cheng, and 葉哲誠. "Integrated transportation planning with the joint replenishment problem." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/15585242786983472718.

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碩士<br>雲林科技大學<br>工業工程與管理研究所碩士班<br>96<br>In two echelon distribution system, common replenishment of single-supplier and multi-retailer is so-called Joint Replenishment Problem (JRP). In traditional distribution system, replenishment decision and transportation planning are decided separately. That means inventory cost and transportation cost are calculated separately - replenishment decision minimizes inventory cost (ordering cost and holding cost) and transportation planning minimizes transportation cost. As oil price increased, the transportation cost raised. The replenishment policy is made
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Book chapters on the topic "Joint replenishment problem (JRP)"

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Cheung, Sin-Shuen. "The Submodular Facility Location Problem and the Submodular Joint Replenishment Problem." In Approximation and Online Algorithms. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-18263-6_7.

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Bienkowski, Marcin, Jaroslaw Byrka, Marek Chrobak, et al. "Approximation Algorithms for the Joint Replenishment Problem with Deadlines." In Automata, Languages, and Programming. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39206-1_12.

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Otero-Palencia, Carlos, Jairo R. Montoya-Torres, and René Amaya-Mier. "On the Complexity of the Collaborative Joint Replenishment Problem." In Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80906-5_22.

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Nonner, Tim, and Maxim Sviridenko. "An Efficient Polynomial-Time Approximation Scheme for the Joint Replenishment Problem." In Integer Programming and Combinatorial Optimization. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36694-9_27.

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Schulz, Andreas S., and Claudio Telha. "Approximation Algorithms and Hardness Results for the Joint Replenishment Problem with Constant Demands." In Algorithms – ESA 2011. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23719-5_53.

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Zapata-Cortes, Julian Andres, Martín Darío Arango-Serna, and Víctor Jaime Saldarriaga-Romero. "The Constrained Joint Replenishment Problem Using Direct and Indirect Grouping Strategies with Genetic Algorithms." In Best Practices in Manufacturing Processes. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99190-0_11.

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Li, C., X. Wang, T. Zhang, and C. Wang. "Joint replenishment and freight problem with fuzzy demand." In Electronic Engineering and Information Science. CRC Press, 2015. http://dx.doi.org/10.1201/b18471-186.

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Li, C., S. Zhao, T. Zhang, and X. Wang. "Reinforcement learning of fuzzy joint replenishment problem in supply chain." In Electronic Engineering and Information Science. CRC Press, 2015. http://dx.doi.org/10.1201/b18471-185.

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Taleizadeh, Ata Allah, and Leopoldo Eduardo Cárdenas-Barrón. "Hybrid Metaheuristics Algorithms for Inventory Management Problems." In Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2086-5.ch011.

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The hybrid metaheuristics algorithms (HMHAs) have gained a considerable attention for their capability to solve difficult problems in different fields of science. This chapter introduces some applications of HMHAs in solving inventory theory problems. Three basic inventory problems, joint replenishment EOQ problem, newsboy problem, and stochastic review problem, in certain and uncertain environments such as stochastic, rough, and fuzzy environments with six different applications, are considered. Several HMHAs such as genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO), harmony search (HS), variable neighborhood search (VNS), and bees colony optimization (BCO) methods are used to solve the inventory problems. The proposed metaheuristics algorithms also are combined with fuzzy simulation, rough simulation, Pareto selecting and goal programming approaches. The computational performance of all of them, on solving these three optimization problems, is compared together.
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Conference papers on the topic "Joint replenishment problem (JRP)"

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Alarcón, Miguel Ángel Marfurt, and Lehilton Lelis Chaves Pedrosa. "Uma Aproximação para o Problema de Reabastecimento em Conjunto com Capacidades." In Encontro de Teoria da Computação. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/etc.2021.16368.

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O Joint Replenishment Problem (JRP) envolve um conjunto de varejistas que enfrentam demandas diárias por um item em um horizonte de planejamento. As demandas são satisfeitas por itens previamente mantidos em estoque e reabastecidos por meio de um pedido conjunto para um depósito de um subconjunto de varejistas. O objetivo é decidir quando fazer os pedidos e quais varejistas serão atendidos em cada pedido, de modo a minimizar os custos totais de entrega e armazenamento. No Tree JRP, a cadeia de fornecimento é representada por uma árvore cujas folhas são os varejistas e o custo de entrega para u
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Liang, Zhijie, Fang Zhao, and Mozhen Cao. "Algorithm of Deterministic Joint Replenishment Problem." In Eighth International Conference of Chinese Logistics and Transportation Professionals (ICCLTP). American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/40996(330)419.

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Li, C. Y., J. Gao, T. W. Zhang, and X. T. Wang. "Differential Evolution Algorithm for Constraint Joint Replenishment Problem." In 2014 8th International Conference on Future Generation Communication and Networking (FGCN). IEEE, 2014. http://dx.doi.org/10.1109/fgcn.2014.23.

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Li Chengyan and Wang Chuang. "Joint replenishment and delivery problem with stochastic demand." In 2015 4th International Conference on Computer Science and Network Technology (ICCSNT). IEEE, 2015. http://dx.doi.org/10.1109/iccsnt.2015.7490719.

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Bienkowski, Marcin, Jaroslaw Byrka, Marek Chrobak, Łukasz Jeż, Dorian Nogneng, and Jiří Sgall. "Better Approximation Bounds for the Joint Replenishment Problem." In Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973402.4.

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Nafisah, Laila, Ahmad Muhsin, Bekti Sulistiyani, and Yuni Siswanti. "Joint Replenishment Problem for Multi Supplier One Regional." In International Conference on Business, Economy, Entrepreneurship and Management. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0009958604010411.

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Wahab, M. I. M., and Y. Chen. "The joint replenishment problem with resource restriction: A note." In 2018 5th International Conference on Industrial Engineering and Applications (ICIEA). IEEE, 2018. http://dx.doi.org/10.1109/iea.2018.8387122.

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Xu, Hui, Shi-Liang Jin, and Yue Hong. "An Algorithm for the Joint Replenishment Problem with Multiple Resource Constraints." In 2007 International Conference on Wireless Communications, Networking and Mobile Computing. IEEE, 2007. http://dx.doi.org/10.1109/wicom.2007.1568.

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Tsao, Yu-Chung, and Lu-Wen Liao. "An Algorithm for Joint Multi-item Replenishment Problem under Trade Credits." In 2010 Second International Conference on Computer and Network Technology. IEEE, 2010. http://dx.doi.org/10.1109/iccnt.2010.117.

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Jiying, Li, and Ji Zhihong. "Joint replenishment problem of military aircraft consumptive items under resource constraint." In 2017 8th International Conference on Mechanical and Aerospace Engineering (ICMAE). IEEE, 2017. http://dx.doi.org/10.1109/icmae.2017.8038750.

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