基于系统动力学的地方政府与制造企业碳减排演化博弈分析

为探究中国在碳减排政策下地方政府与制造企业双方的博弈关系,在分析地方政府和制造企业不同策略下的成本和收益的基础上,采用系统动力学方法构建了地方政府和制造企业之间的静态混合策略演化博弈模型;进一步引入政府动态惩罚和补偿策略,剖析政企双方策略的互动机制。分析结果表明:地方政府对企业是否采取碳减排措施的奖惩力度、企业采取碳减排措施的成本与收益,会直接影响博弈结果;地方政府和制造企业两个群体在三种情况下存在演化稳定策略;在一定条件下,系统演化呈现周期性特征;当地方政府实施动态惩罚或补偿措施时,该博弈模型存在稳定的Nash均衡点。     

Application of fuzzy compromise solution method for fit concept selection

The modern manufacturing environment is highly turbulent so as to satisfy the dynamic needs of customers’. To enable the achievement of competitiveness in this complex business environment, newer manufacturing strategies have been introduced for enabling waste elimination and enhancing flexibility and responsiveness of systems. Fit manufacturing is a competitive manufacturing paradigm which includes lean and agile systems coupled with sustainable benefits. This article presents a study in which the concept selection in fit environment was formulated as Multi Criteria Decision Making (MCDM) problem and solved using fuzzy based compromise solution method, Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The selected concept design of automotive component was subjected to implementation in the case organisation.     

An agent-based model of organizational ambidexterity decisions and strategies in new product development

Organizational ambidexterity, defined as the pursuit of both exploitation and exploration, has become an important topic in the study of organizations, especially in innovation management theory. Previous literature has not focused on the strategic (game-theoretic) aspects of organizational ambidexterity or on its decision-making aspects. Little is known about how or even whether the decision to adopt ambidexterity is competitively advantageous in the presence of diverse strategies that competitors may adopt. This facet of the subject is inherently game-theoretic; the value of a decision by one firm depends in part on decisions made by other firms. This paper initiates systematic investigation of these strategic aspects, including the overall performance of available strategies. Specifically, this study examines questions of ambidexterity-related strategy performance in the context of new product development. The main contributions are (1) to introduce and make available to the research community an agent-based model and decision support system that captures many of the key aspects and tradeoffs, which have been identified in the literature, of the exploration–exploitation dilemma faced by firms in the new product development process, with a focus on organizations’ product investment decisions and (2) to report on results obtained from the model, calibrated with available data from the literature, augmented by new data collected from interviews with practitioners.     

STAR-GARCH模型与股票市场投资策略非线性

本文首次基于投资者异质性和行为金融理论,从投资者风险偏好的角度度量市场情绪,应用STAR-GARCH模型,对我国股票市场投资策略的非线性转换进行了实证研究。研究结果表明:(1)我国股票市场投资策略表现出明显的两机制,说明我国股票市场存在显著的投资者异质性;(2)当市场情绪指数分别为0.06和0.046时,沪深股票投资策略处于中间机制,表现为偏向理性投资策略,而当市场情绪指数大于约0.6或小于约-0.5时,沪深股票投资策略处于外机制,表现为偏向噪音交易策略,在两种机制间,存在着投资策略的非线性转换;(3)当沪深股票投资策略处于中间机制时,股票市场日收益率平均波动更小,因而表现得更稳定。     

The Relationship Between Stock Markets Of Major Developed Countries And Asian Emerging Markets

With the emergence of new capital markets and liberalization of stock markets in recent years, there has been an increase in investors' interest in international diversification. This is so because international diversification allows investors to have a larger basket of foreign securities to choose from as part of their portfolio assets, so as to enhance the reward-to-volatility ratio. This benefit would be limited if national equity markets tend to move together in the long run. This paper thus studies the issue of co-movement between stock markets in major developed countries and those in Asian emerging markets using the concept of cointegration. We find that there is co-movement between some of the developed and emerging markets, but some emerging markets do differ from the developed markets with which they share a long-run equilibrium relationship. Furthermore, it has been observed that there has been increasing interdependence between most of the developed and emerging markets since the 1987 Stock Market Crash. This interdependence intensified after the 1997 Asian Financial Crisis. With this phenomenon of increasing co-movement between developed and emerging stock markets, the benefits of international diversification become limited.     

基于模糊数的政府与绿色制造商博弈分析

近年来环境问题已经成为人们迫切需要解决的重要问题,促使制造商采取绿色制造模式也是各国政府正在面临的一大难题。因此文章结合三角模糊数与博弈理论建立了政府与绿色制造商的模糊博弈模型,将博弈结果分为纯策略和混合策略两类,并讨论了各种情形下政府与绿色制造商的不同策略以及影响因素,分析了最优博弈结果以及相应的管理策略,为绿色制造模式的顺利实施提供了相关建议。研究结果表明,政府的补贴和惩罚等策略在绿色制造模式的采取方面起着举足轻重的作用。最后利用三角结构元法对算例分纯策略和混合策略两种情况进行分析求解,从而验证了结论的正确性和可行性。     

Metaheuristics for a Flexible Assembly System Design Problem

Flexibility has become an important priority in the formulation and implementation of manufacturing strategies. This in turn has opened up a new class of design problems for such systems. Flexible assembly systems (FAS), consisting of a variety of processors and operations, provide the opportunity for improving product manufacturing flexibility, hence gaining competitive advantages. This paper considers a particular design decision problem for FAS. A matrix-based, polynomial-time lower bound algorithm is presented. Simulated annealing and tabu search metaheuristics are formulated to address the problems. Computational experience with these metaheuristics is reported.     

The adoption of environmental and risk management practices: Relationships to environmental performance

The Strategic Goals Program sponsored by the United States Environmental Protection Agency which focuses on the Metal Finishing Industry is used to investigate some pertinent issues related to small manufacturing enterprises' environmental performance. Results from the initial years of this program are used to evaluate a number of hypotheses related to the relationship between environmental performance and adoption of environmental and risk management practices, especially among smaller organizations. The methodology uses unique structuring of data to determine temporal environmental performance using data envelopment analysis. Results show that early and increased investment in these practices and programs may not provide for better performance benefits. The findings have implications for environmental managers in smaller organizations and policy makers overseeing these types of organizations.     

Exploring strategy use and strategy flexibility in non-routine problem solving by primary school high achievers in mathematics

Many researchers have investigated flexibility of strategies in various mathematical domains. This study investigates strategy use and strategy flexibility, as well as their relations with performance in non-routine problem solving. In this context, we propose and investigate two types of strategy flexibility, namely inter-task flexibility (changing strategies across problems) and intra-task flexibility (changing strategies within problems). Data were collected on three non-routine problems from 152 Dutch students in grade 4 (age 9–10) with high mathematics scores. Findings showed that students rarely applied heuristic strategies in solving the problems. Among these strategies, the trial-and-error strategy was found to have a general potential to lead to success. The two types of flexibility were not displayed to a large extent in students’ strategic behavior. However, on the one hand, students who showed inter-task strategy flexibility were more successful than students who persevered with the same strategy. On the other hand, contrary to our expectations, intra-task strategy flexibility did not support the students in reaching the correct answer. This stemmed from the construction of an incomplete mental representation of the problems by the students. Findings are discussed and suggestions for further research are made.     

A quantum-behaved simulated annealing algorithm-based moth-flame optimization method

This study develops an improved moth-flame optimization algorithm, which is a recently proposed optimizer based on moth behavior in nature. It has achieved favorable results in medical science, educational evaluation, and other fields. However, the convergence rate of the original moth-flame optimization algorithm is too fast in the running process, and it is prone to fall into local optimum, which leads to the failure to produce the high-quality optimal result. Accordingly, this paper proposes a reinforced technique for the moth-flame optimization algorithm. Firstly, the simulated annealing strategy is introduced into the moth-flame optimization algorithm to boost the advantage of the algorithm in the local exploitation process. Then, the idea of the quantum rotation gate is integrated to enhance the global exploration ability of the algorithm and ameliorate the diversity of the moth. These two steps maintain the relationship between exploitation and exploration as well as strengthen the performance of the algorithm in both phases. After that, the method is compared with ten well-regarded and ten alternative algorithms on benchmark functions to verify the effectiveness of the approach. Also, the Wilcoxon signed rank and Friedman assessment were performed to verify the significance of the proposed method against other counterparts. The simulation results reveal that the two introduced strategies significantly improve the exploration and exploitation capacity of moth-flame optimization algorithm. Finally, the algorithm is utilized to feature selection and two engineering problems, including pressure vessel design and multiple disk clutch brake problems. In these practical applications, the novel algorithm also achieves particularly notable results, which also illustrates that the algorithm is qualified is an effective auxiliary appliance in solving complex optimization problems.     

投资组合保险CPPI策略研究

随着期权理论应用的发展,投资组合保险在国外已成为一种盛行的资产配置策略, 常数比例投资组合保险策略(CPPI)以其模型简单、参数的设置又能充分反映投资人不同的风险偏好、而且易于实施,成为大型安全型基金的基金经理首选的投资策略.本文研究并推广了CPPI策略,找出CPPI与期权的关系,讨论了借贷限制对(CPPI策略的影响,最后对CPPI策略在中国市场的可投资性进行了评测.     

Infinite-Dimensional Compressed Sensing and Function Interpolation

We introduce and analyse a framework for function interpolation using compressed sensing. This framework—which is based on weighted \(\ell ^1\) minimization—does not require a priori bounds on the expansion tail in either its implementation or its theoretical guarantees and in the absence of noise leads to genuinely interpolatory approximations. We also establish a new recovery guarantee for compressed sensing with weighted \(\ell ^1\) minimization based on this framework. This guarantee conveys several benefits. First, unlike existing results, it is sharp (up to constants and log factors) for large classes of functions regardless of the choice of weights. Second, by examining the measurement condition in the recovery guarantee, we are able to suggest a good overall strategy for selecting the weights. In particular, when applied to the important case of multivariate approximation with orthogonal polynomials, this weighting strategy leads to provably optimal estimates on the number of measurements required, whenever the support set of the significant coefficients is a so-called lower set. Finally, this guarantee can also be used to theoretically confirm the benefits of alternative weighting strategies where the weights are chosen based on prior support information. This provides a theoretical basis for a number of recent numerical studies showing the effectiveness of such approaches.     

Adaptive brainstorm optimisation with multiple strategies

Brainstorm optimisation (BSO) algorithm is a recently developed swarm intelligence algorithm inspired by the human problem-solving process. BSO has been shown to be an efficient method for creating better ideas to deal with complex problems. The original BSO suffers from low convergence and is easily trapped in local optima due to the improper balance between global exploration and local exploitation. Motivated by the memetic framework, an adaptive BSO with two complementary strategies (AMBSO) is proposed in this study. In AMBSO, a differential-based mutation technique is designed for global exploration improvement and a sub-gradient strategy is integrated for local exploitation enhancement. To dynamically trigger the appropriate strategy, an adaptive selection mechanism based on historical effectiveness is developed. The proposed algorithm is tested on 30 benchmark functions with various properties, such as unimodal, multimodal, shifted and rotated problems, in dimensions of 10, 30 and 50 to verify their scalable performance. Six state-of-the-art optimisation algorithms are included for comparison. Experimental results indicate the effectiveness of AMBSO in terms of solution quality and convergence speed.     

Application of consistent fuzzy preference relations in predicting the success of knowledge management implementation

The implementation of knowledge management (KM) involves innovation and reformation for organizations. KM implementation requires not only a substantial investment, but also changes the organization culture and structure. Before embarking on KM, thorough planning is crucial to ensure the implementation achieves the intended objectives of accruing profit and enhancing competitiveness for organisations. Therefore, this study proposes an analytic hierarchical prediction model based on the reciprocal additive consistent fuzzy preference relations to help the organizations become aware of the essential factors affecting the KM implementation, forecasting the chance of successful KM initiative, as well as identifying the actions necessary before implementing KM. Pairwise comparisons are used to determine the priority weights of influential factors and the ratings of two possible outcomes (success and failure) amongst decision makers. The subjectivity and vagueness in the prediction procedures are dealt with using linguistic terms quantified in an interval scale [0, 1]. By multiplying the weights of influential factors and the ratings of possible outcomes, predicted success/failure values are obtained to enable organizations to decide whether to initiate knowledge management, inhibit adoption or take remedial actions to increase the possibility of successful KM project. This proposed approach is demonstrated with a real case study assessed by eleven evaluators solicited from a Liquid Crystal Display (LCD) manufacturing corporation located in Taiwan.     

Supplier selection in supplier chain management using Choquet integral-based linguistic operators under fuzzy heterogeneous environment

The fierce competition and the globalization of the market economy urge manufacturing organizations to adopt advanced manufacturing paradigms for sustaining in the global markets. Supply chain management is an essential ingredient of advanced manufacturing systems and finding those partners with the best fit to the existing supply chain is a vital issue concerned in the process of managing supply chains. Due to the decision maker’s knowledge field and the nature of evaluated attributes, assessments are always with different formats, which were first unified into the linguistic terms in the standard linguistic set. Two additive fuzzy measures were used to model criteria interactions by pairs and to derive the special expressions of Marichal entropy and Choquet integral, which is more convenient to use in practice. Fuzzy measures were identified based on the maximum of Marichal entropy. The decision making procedure was illustrated taking an automobile manufacturing industry as an example, compared with the other methods, and showed the feasibilities and advantages. The inadequacies as well as the further research directions were proposed.     

Optimal procurement strategies for online spot markets

Spot markets have emerged for a broad range of commodities, and companies have started to use them in addition to their traditional, long-term procurement contracts (forward contracts). In comparison to forward contracts, spot markets offer products at essentially negligible lead time, but typically command a higher expected price for this added flexibility while also exhibiting substantial price uncertainty. In our research, we analyze the resulting procurement challenge and quantify the benefits of using spot markets from a supply chain perspective. We develop and solve mathematical models that determine the optimal order quantity to purchase via forward contracts and the optimal quantity to purchase via spot markets. We analyze the most general situation where commodities can be both bought and sold via a spot market and derive closed-form results for this case. We compare the obtained results to the reference scenario of pure contract sourcing and we include results for situations where the use of spot markets is restricted to either buying or selling only. Our approaches can be used by decision makers to determine optimal procurement strategies based on key parameters such as, demand and spot price volatilities, correlation between demand and spot prices, and risk aversion. The results of our analysis demonstrate that significant profit improvements can be achieved if a moderate fraction of the commodity demand is procured via spot markets. The results also show that companies who use spot markets can offer a higher expected service level, but that they might experience a higher variability in profits than companies who do not use spot markets. We illustrate our analytical results with numerical examples throughout the paper.     

Implementation of Lean Six Sigma in small- and medium-sized manufacturing enterprises in the Netherlands

In this paper we provide an exploration and analysis of Lean Six Sigma (LSS) implementation in Dutch manufacturing/engineering small- and medium-sized enterprises (SMEs). Critical success factors (CSFs) and impeding factors are identified and analysed. Exploratory empirical evidence about LSS implementation in Dutch SMEs was collected from a survey study on Dutch SMEs. Statistical testing was applied to validate the ranking of the CSFs. To deepen insight in how organizations translate CSFs into practice and cope with impeding factors, additional in-depth qualitative information was gathered from six case studies. Linking to customer, vision and plan statement, communication and management involvement and participation are the highest ranked CSFs. Internal resistance, the availability of resources, changing business focus and lack of leadership are the strongest impeding factors. The case studies confirmed the importance of the CSFs and revealed three new CSFs: personal LSS-experience of Top management, development of the project leader's soft skills and supply chain focus. SMEs in the Netherlands make no distinct separation between lean manufacturing and Six Sigma, but rather apply both approaches intertwined.     

Product concept and prototype flexibility in manufacturing: Implications for customer satisfaction

A rapidly changing competitive landscape and dynamic customer expectations require manufacturing firms to seek flexibility in product development. Product concept flexibility (i.e., developing design options) and product prototype flexibility (i.e., creating working models) emerge as effective ways to quickly develop new products that meet competitive challenges and satisfy customer demands. Product concept flexibility enables firms to fully explore various product definitions and ideas. Product prototype flexibility allows firms to gather customers’ feedback and investigate design feasibility. Using data from 273 manufacturing firms, this research tests mediating, moderating, and additive models that relate product concept flexibility, product prototype flexibility, and customer satisfaction. The results indicate that firms with high product concept flexibility are more likely to benefit from prototype flexibility than firms with low product concept flexibility, and that product concept flexibility and product prototype flexibility act independently and additively to predict customer satisfaction.     

On the Role of Mixed Strategies in Elementary Decision Analysis and Related Decision-Support-System Treatments

We first demonstrate that mixed strategies are relevant in decision analysis for a maximin decision-maker quite apart from any game-theory considerations. This rectifies the apparent misconception that results from MS/OR textbooks which discuss mixed strategies only in the game-theory setting. Next we show an example of an implementable mixed strategy, by which we mean a mixed decision strategy which does not require randomization for its implementation. This application is to portfolio construction.