A hybrid approach to configure eco-efficient supply chains under consideration of performance and risk aspects

Formal models that support multi-criteria decision making represent a strongly growing area in sustainable supply chain management research. However, uncertainties and risks are seldom considered in quantitative models for green supply chain (SC) design. The paper at hand suggests a hybrid approach to configure an eco-efficient SC for a new product under consideration of economic and environmental risks. Discrete-event simulation is applied to assess the financial, operational and environmental performance of different SC configuration options while the value-at-risk concept is adapted to evaluate related SC risks. The analytic hierarchy process is employed to solve the resulting multi-criteria decision problem of choosing the best option. The approach is illustrated at a case example of a fast moving consumer goods manufacturer.     

流程、合规与操作风险管理

商业银行风险管理研究中“违规活动—操作风险—信用风险”风险链条尚未得到足够重视． 巴塞尔委员会全面风险管理框架下的众多风险是分层次的，最底层是合规与操作风险，合规与操作风险做到位能极大降低其他风险发生的概率． 以往由于缺少数据支撑，信用风险的合规与操作风险动因无法建立，本文基于“流程—节点—风险点—控制措施—违规事件”关联模型，建立了合规与操作风险的动因库和损失数据库，并在理论上对风险链条上的风险传递关系进行初步探索． 首先基于流程对合规与操作风险动因进行解析，寻找深层次的人员违规和操作风险动因; 其次，探讨了金融机构如何通过业务流程再造改善合规与操作风险管理; 最后是基于流程的操作风险量化建模． 基于实践，总结提炼了“三位一体”的金融机构合规与操作风险管理模式，包含理论基础、信息系统和保障机制，该模式在诸多金融机构中得到运用，并取得显著成效．     

Bid-rigging networks and state-corporate crime in the construction industry

This study highlights the symbiotic relationship that may arise between political and business actors in conspiracies organized around public construction bids. Based on a core-periphery social network analysis, the study tracks the emergence of such a conspiracy in the city of Laval (Canada) by illustrating the evolution of bid-rigging networks revolving around suspected and persistent acts of corruption, bid-rigging, and bribery. To assess this process, the study monitors irregular bidding indicators across a data set compiled from more than 7000 public construction tenders that were processed by the city from 1966 to 2013. Findings reveal that firms suspected of bid-rigging activities were perennial core participants largely as a result of a state-corporate crime system that served as the guiding force for agreements between the main construction entrepreneurs.     

Cloud manufacturing system for sheet metal processing

Abstract

Cloud computing is changing the way industries and enterprises run their businesses. Cloud manufacturing is emerging as an approach to transform the traditional manufacturing business model, while helping the manufacturer to align production efficiency with its business strategy, and creating intelligent factory networks that enable collaboration across the whole enterprise. Many production planning and control (PPC) problems are essentially optimisation problems, where the objective is to develop a plan that meets the demand at minimum cost or maximum profit. Because the underlying optimisation problem will vary in the different business and operation phases, it is important to think about optimisation in a dynamic mechanism and in a number of interlinked sub-problems at the same time. Cloud manufacturing has the potential to offer decision support as a service and medium of communication in PPC. To solve these problems and produce collaboration across the supply chain, this paper provides an overview of the state of the art in cloud manufacturing and presents a model of cloud-based production planning and production system for sheet metal processing.     

Evaluation of multi-objective optimization approaches for solving green supply chain design problems

This paper evaluates the applicability of different multi-objective optimization methods for environmentally conscious supply chain design. We analyze a case study with three objectives: costs, CO₂ and fine dust (also known as PM – Particulate Matters) emissions. We approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods with pre-defined or adaptively selected parameters, two popular evolutionary algorithms, SPEA2 and NSGA-II, with different selection strategies, and their interactive counterparts that incorporate Decision Maker׳s (DM׳s) indirect preferences into the search process. Within this case study, the CO₂ emissions could be lowered significantly by accepting a marginal increase of costs over their global minimum. NSGA-II and SPEA2 enabled faster estimation of the Pareto front, but produced significantly worse solutions than the exact optimization methods. The interactive methods outperformed their a posteriori counterparts, and could discover solutions corresponding better to the DM preferences. In addition, by adjusting appropriately the elicitation interval and starting generation of the elicitation, the number of pairwise comparisons needed by the interactive evolutionary methods to construct a satisfactory solution could be decreased.     

A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing

This paper investigates an integrated production and transportation scheduling problem in an MTO supply chain. A harmony search-based memetic optimization model is developed to handle this problem, in which certain heuristic procedures are proposed to convert the investigated problem into an order assignment problem. A novel improvisation process is also proposed to improve the optimum-seeking performance. The effectiveness of the proposed model is validated by numerical experiments. The experimental results show that (1) the proposed model can solve the investigated problem effectively and that (2) the proposed memetic optimization process exhibits better optimum-seeking performance than genetic algorithm-based and traditional memetic optimization processes.     

An oracle-based algorithm for robust planning of production routing problems in closed-loop supply chains of beverage glass bottles

The demand for glass bottles is exhibiting an upward trend over time. The manufacturing of glass bottles is costlier in terms of time and resources and is associated with a higher level of heat generation and environmental pollution compared to recycling processes. In response to the aforementioned challenges, companies that use glass bottles need to implement strategies to manage their reverse supply chains in conjunction with their traditional supply chains, as the economic and environmental benefits of returned products are unquestionable. Closed-loop supply chains (CLSCs) integrate forward and reverse flows of products and information. This integration helps companies to have a broader view of the whole chain. Despite these advantages, managing CLSCs can be challenging as they are exposed to many uncertainties regarding supply and demand processes, travel times, and quantity/quality of returned products.In this study, we consider the production planning, inventory management, and vehicle routing decisions of a CLSC of beverage glass bottles. We propose an MILP model and rely on a multi-stage adjustable robust optimization (ARO) formulation to deal with the randomness in both the demand for filled bottles and the requests for pickups of empty bottles. We develop an exact oracle-based algorithm to solve the ARO problem and propose a heuristic search algorithm to reduce the solution time. Our numerical experiments not only show the incompetency of the customary method, namely the affine decision rule approach, but also illustrate how our algorithms can solve the small-size problems and significantly improve the quality of the obtained solution for large problems. Furthermore, our numerical results show that robust plans tend to be sparse, meaning the routes are chosen so that empty bottles are transported to production sites in such a way that fewer new bottles need to be ordered. Thus, robust planning makes the CLSCs more environmentally friendly.     

房价变动、产业转移与区域协调发展——以京津冀地区为例

构建房价-资本模型，分析房地产行业投资收益对工业再投资的影响，发现：地区间适当的房地产行业投资收益差异有利于工业企业从核心地区向边缘地区转移，差异较大则导致资本流向房价增长过快地区的房地产行业；若地区间房地产行业投资收益差异既定，较大的经济发展差距对产业转移起阻碍作用，激烈的市场竞争则起促进作用。利用京津冀地区13个城市的数据构建面板门限模型，验证了：（1）较低的房价增长率促进了北京市相对低效的资本向外转移，但是北京市与周边地区较大的经济发展差距又阻碍了该趋势。（2）核心区流出的资本优先向次发达地区转移，而落后地区则有被彻底边缘化的风险。为实现京津冀地区协调发展，一方面要加强对京津冀地区房价的宏观调控、防止房价过快增长；另一方面要制定针对边缘地区的优惠政策，引导非首都功能向周边转移。     

Hesitant Madams in a Global City: Japanese Expat Wives and their Global Householding in Hong Kong

Care work, once a sanctioned labor of love, is increasingly commodified in transnational contexts. The picture of migrant women shouldering the housework and child care of local professonal women may seem like a mutually beneficial arrangement—matching the “needs” of the haves and have-nots—, but the global care chain ultimately works to maintain the traditional gendered division of labor as well as global inequality. To this trend of globalization of care work, Japan has been an exception; however, how much longer it will be so is now in a question, as the government paves the way for importing domestic labor from abroad. This article focuses on Japanese expat wives in Hong Kong in order to locate Japanese women vis-à-vis the global care chain. The narrative analysis on how they decide whether to hire a domestic worker in their home away from home highlights the sociopolitical nature of their supposedly private choices. Some drew on cultural ideal of wifehood and motherhood to rationalize their choice while others referred to racialized or even overtly racist and classist images of foreign domestic workers. A few women spoke against the system itself, showing awareness of its inherent social injustice. All such narratives are never purely personal; their decisions and the rationalization behind them sustain the prevailing discourses of gender, race, ethnicity, culture, and class, which, in turn, envelop their attempts at global householding.     

Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model

Time-varying GARCH-M models are commonly employed in econometrics and financial economics. Yet the recursive nature of the conditional variance makes likelihood analysis of these models computationally infeasible. This article outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only O(T) computational operations, where T is the sample size. Furthermore, the theoretical dynamic properties of a time-varying-parameter EGARCH(1,1)-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets.