• Journal of Distribution Science
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• v.12 no.3
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• pp.85-98
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• 2014

Purpose - This study primarily aims to represent the current trend of research on CPFR as a promising supply chain collaboration program and proposes a new framework for analyzing any collaboration programs in terms of three key collaborative features. Research design, data, and methodology - This study employs a literature review of selected studies that conduct research on CPFR. CPFR is analyzed based on the proposed framework that characterizes collaboration programs in terms of three key collaborative features. Results - The analysis based on the proposed framework reveals that the current form of CPFR continues to have some collaborative features that are not fully utilized to create an advanced collaboration program. The literature review indicates that most past studies ignore critical issues including the dynamic nature of the multiple-stage supply chain system and negotiation process for collaborative agreement in CPFR implementation. Conclusions - Results indicate that CPFR can become a better supply chain collaboration program by incorporating coordinative cost payment and joint decision making processes. Based on observations on the existing literature of CPFR, this study indicates several important issues to be addressed by future studies.

• Journal of applied mathematics & informatics
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• v.8 no.2
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• pp.519-530
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• 2001

A two commodity continuous review inventory system with independent Poisson processes for the demands is considered in this paper. The maximum inventory level for the i-th commodity fixed as $S_i$(i = 1,2). The net inventory level at time t for the i-th commodity is denoted by $I_i(t),\;i\;=\;1,2$. If the total net inventory level $I(t)\;=\;I_1(t)+I_2(t)$ drops to a prefixed level s $[{\leq}\;\frac{({S_1}-2}{2}\;or\;\frac{({S_2}-2}{2}]$, an order will be placed for $(S_{i}-s)$ units of i-th commodity(i=1,2). The probability distribution for inventory level and mean reorders and shortage rates in the steady state are computed. Numerical illustrations of the results are also provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3412-3432
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• 2019

Recent advances in radio frequency (RF) power transfer provide a promising technology to power sensor nodes. Adoption of mobile chargers to replenish the nodes' energy has recently attracted a lot of attention and the mobility assisted energy replenishment provides predictable and sustained power service. In this paper, we study the joint optimization of mobile charging and data gathering in sensor networks. A wireless multi-functional vehicle (WMV) is employed and periodically moves along specified trajectories, charge the sensors and gather the sensed data via one-hop communication. The objective of this paper is to maximize the uplink throughput by optimally allocating the time for the downlink wireless energy transfer by the WMV and the uplink transmissions of different sensors. We consider two scenarios where the WMV moves in a straight line and around a circle. By time discretization, the optimization problem is formulated as a 0-1 programming problem. We obtain the upper and lower bounds of the problem by converting the original 0-1 programming problem into a linear programming problem and then obtain the optimal solution by using branch and bound algorithm. We further prove that the network throughput is independent of the WMV's velocity under certain conditions. Performance of our proposed algorithm is evaluated through extensive simulations. The results validate the correctness of our proposed theorems and demonstrate that our algorithm outperforms two baseline algorithms in achieved throughput under different settings.