Research in closed-loop supply chains (CLSCs) has grown rapidly over the last 10 years. The authors offer a critical review of influential CLSC research that takes a business economics perspective. Much of the research was inspired by practice-driven thoughtpieces, and this helped to keep research focused on relevant issues. However, CLSC research has several assumptions, such as perfect substitution between new and remanufactured products that risk becoming institutionalized. There is a strong need to carefully examine current industrial practice so that research remains focused on relevant problems. Deeper understanding of consumer perceptions of remanufactured products, product diffusion, and valuation of returned products are needed for the field to continue to add insights into developing sustainable economies.

Production and Operations Management

１ インフラを構築する（ＡＷＳにおけるインフラ；ＶＰＣを構成する；ＶＰＣとオンプレミス環境とを接続する） ２ ファイルオブジェクトを保存・共有・公開する（オブジェクトストレージＳ３の機能；ファイルストレージとして利用する；Ｗｅｂサーバーを構築する；信頼性とコストのバランスをとりたい） ３ アプリケーションサーバーを構築する（Ａｍａｚｏｎ ＥＣ２とＡＷＳ Ｌａｍｂｄａ；スケーラビリティーを高める；サーバーレスでプログラムを動かす；データベースサービスを活用する） ４ ＡＷＳシステムを管理する（リソース監視と異常検知・通報；耐障害性を高める仕組みとバックアップ＆リカバリー；構成管理）

Amazon Web Services完全ソリューションガイド

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Supermodularity And Complementarity

基於Google Cloud Platform設計高效能日誌分析平台之研究

In large and complex networks such as the Internet and road networks, traffic routing is typically decentralized. Users in the network choose their routes independently to minimize their own delay, leading to complicated and nonintuitive outcomes that differ significantly from the outcome obtained if traffic is centrally routed. A widely used technique of analyzing traffic in these networks is to model traffic as a routing game between the users. Routing games are a popular tool to analyze traffic in complex networks since they naturally capture the competition that arises between users seeking to utilize network resources to minimize their own delay. We study equilibria in different models of routing games corresponding to different applications, and present a number of fundamental results about equilibria. We first study routing games where players control significant flow that is split along multiple paths, called atomic splittable routing games. We give the first examples of multiple equilibria in these games, and further give a topological characterization of atomic splittable routing games with unique equilibria. In contrast, in nonatomic routing games, where each player controls infinitesimal flow, the equilibrium is known to be essentially unique. Players in a routing game often form coalitions, and equilibria obtained in the presence of such coalitions can differ significantly from the equilibria obtained without coalitions. We study the impact such coalitions have on the total delay of the players in nonatomic routing games. In series-parallel graphs, we show that the formation of coalitions always reduces the total delay of the players at equilibrium. We then study a model of routing games where flows travel through the network over time, as compared to previous models where flow is assumed to be static. In this more realistic model, we give an efficiently computable Stackelberg strategy and show that the equilibrium under this strategy is no worse than a small constant times the optimal, for two natural measures of optimality.

Routing games

In this paper, we study the problem of designing new mechanisms for selling reserved instances (also referred to as virtual machines) in cloud computing. Unlike the practice in today's clouds in which users only have a few predefined options to reserve instances (i.e., either 1-year reservation or 3-year reservation), we allow users to reserve resources for any length and from any time point in the future. Our goal is to maximize the social welfare. We propose two mechanisms, one for the case where all the jobs are tight (their lengths are exactly their reservation time intervals), and the other for the more general case where jobs are delayable and have some flexibility on their reservations. Both of the mechanisms are prompt in the sense that the acceptance and the payment for a job is determined at the very moment of its arrival. We use competitive analysis to evaluate the performance of our mechanisms, and show that both of the mechanisms have a competitive ratio of O(ln(kT)) under some mild assumption, where k (res. T) is the maximum ratio between per-instance-hour valuation (res. length) of any two jobs. We then prove that no algorithm can achieve a competitive ratio better than ln(2kT) under the same assumption. Therefore, our mechanisms are optimal within a constant factor.

/pdf/selling-reserved-instances-in-cloud-computing-4y1a0mwsnv.pdf

Selling reserved instances in cloud computing

Locating source of diffusion in networks is crucial for controlling and preventing epidemic risks. It has been studied under various probabilistic models. In this paper, we study source location from a deterministic point of view by modeling it as the minimum weighted doubly resolving set (DRS) problem, which is a strengthening of the well-known metric dimension problem. 
Let $G$ be a vertex weighted undirected graph on $n$ vertices. A vertex subset $S$ of $G$ is DRS of $G$ if for every pair of vertices $u,v$ in $G$, there exist $x,y\in S$ such that the difference of distances (in terms of number of edges) between $u$ and $x,y$ is not equal to the difference of distances between $v$ and $x,y$. The minimum weighted DRS problem consists of finding a DRS in $G$ with minimum total weight. We establish $\Theta(\ln n)$ approximability of the minimum DRS problem on general graphs for both weighted and unweighted versions. This is the first work providing explicit approximation lower and upper bounds for minimum (weighted) DRS problem, which are nearly tight. Moreover, we design first known strongly polynomial time algorithms for the minimum weighted DRS problem on general wheels and trees with additional constant $k\ge0$ edges.

Approximability of the Minimum Weighted Doubly Resolving Set Problem

Locating source of diffusion in networks is crucial for controlling and preventing epidemic risks. It has been studied under various probabilistic models. In this paper, we study source location from a deterministic point of view by modeling it as the minimum weighted doubly resolving set problem, which is a strengthening of the well-known metric dimension problem.

Selfish routing is one of the fundamental models in the study of network traffic systems. While most literature assumes essentially static flows, game theoretical models of dynamic flows began to draw attention recently [1, 5]. We study a new dynamic flow game with atomic agents. The game is played over an acyclic directed network, with two special vertices called the origin o and the destination d, respectively, such that each edge is on at least one o-d path. Each edge of this network is associated with an integer capacity and a positive integer free-flow transit cost. Time horizon is infinite and discretized as 1,2,…. At each time point, a set of selfish agents enter the network from the origin, trying to reach the destination as quickly as possible. When an agent uses an edge, two costs are incurred to him: the fixed transit cost of the edge and a variable waiting cost dependent on the volume of the traffic flow on that edge and the edge capacity as well as the agent's position in the queue of agents waiting at that edge. The total cost to each agent, the latency he experiences in the network, is the sum of the two costs on all edges he uses (which form an o-d path in the network).

Changjun Wang

Papers

Selling reserved instances in cloud computing

Approximability of the Minimum Weighted Doubly Resolving Set Problem

Approximability of the Minimum Weighted Doubly Resolving Set Problem

A Network Game of Dynamic Traffic

Approximation for the minimum cost doubly resolving set problem