A nonlinear approach to a class of combinatorial optimization problems

A special class of combinatorial optimization problems is considered. We develop a compact nonconvex quadratic model for these problems that incorporates all inequality constraints in the objective function, and discuss two approximation algorithms for solving this model. One is inspired by Karmarkar's potential reduction algorithm for solving combinatorial optimization problems; the other is a variant of the reduced gradient method. The paper concludes with computational experiences with both real-life and randomly generated instances of the frequency assignment problem. Large problems are satisfactorily solved in reasonable computation times.     

A polynomial goal programming approach to a class of quality control problems

The traditional quality control approach based on statistical tools has been very useful and effective when output and input qualities can be denned in terms of a single characteristic. However, in process industries such as paper, the output quality is denned in terms of two or more distinct characteristics; hence, reducing the deviation of one output characteristic from its permissible limits could result in forcing other output and/or input characteristics to deviate from their respective limits. Compounding this phenomenon is the fact that most of these industries produce substantial amounts of pollutants whose characteristics are a function of the input and output characteristics. Thus, with increasing costs of waste treatment and stringent pollution standards, there arises a notion of a trade-off between attaining market specified output characteristics and meeting federally regulated pollution standards.In this article a general process quality control problem has been formulated that reflects the above trade-off both in terms of a linear and a polynomial goal programming problem. Major advantages and differences between the two formulations are highlighted and illustrated with a practical example drawn from the paper industry.Three separate cases each with different priorities assigned to the output, pollutant and input characteristics are developed and solved under both formulations. Based on the analysis it is observed that the different solutions that result are contingent on the assumptions concerning the priorities associated with each goal and the manner by which one chooses to incorporate tradeoffs between goals in the objective function. Additionally, it is found that the solutions obtained under polynomial goal programming formulation are more conducive for implementation in practical quality control contexts.     

On the strategic use of risk and undesirable goods in multidimensional screening

A monopolist sells goods possibly with a characteristic consumers dislike (for instance, he sells random goods to risk averse agents), which does not affect the production costs. We investigate the question whether using undesirable goods is profitable to the seller. We prove that in general this may be the case, depending somehow on the correlation between agent types and aversion. This is due to screening effects that outperform this aversion. We analyze, in a continuous framework, several multidimensional cases.     

Pricing the cloud: a QoS-based auction approach

ABSTRACT

Cloud computing is an evolutionary technology that offers on-demand resources and elastic services through the Internet. Most providers adopt fixed-price mechanisms (e.g. pay-as-you-go). However, a few providers have recently employed auction-like approaches to price cloud services. Meanwhile, cloud consumers pay more attention to Quality of Service (QoS) such as availability, which measures how well a service is performed. This paper proposes a novel auction approach that can efficiently allocate resources according to customers’ QoS preferences. The QoS-based pricing can generate more revenue than a fixed-price strategy. This research lies at the intersection of cloud computing, economics, and information systems.     

A multi-stage stochastic programming approach for pre-positioning of relief supplies considering returns

A dynamic pre-positioning problem is proposed to efficiently respond to victims’ need for relief supplies under uncertain and dynamic demand in humanitarian relief. The problem is formulated as a multi-stage stochastic programming model that considers pre-positioning with the dynamic procurement and return decisions about relief supplies over a time horizon. To validate the advantages of dynamic pre-positioning, three additional pre-positioning strategies are presented: pre-positioning with one-time procurement and without returns, pre-positioning with one-time procurement and returns, and pre-positioning with dynamic procurement and without returns. Using data from real-world disasters in the United States in the Emergency Events Database, we present a numerical analysis to study the applicability of the proposed models. We develop a sample average approximation approach to solving the proposed model in large-scale cases. Our main contribution is that we integrate dynamic procurement and return strategies into pre-positioning to decrease both costs and shortage risks in uncertain and dynamic contexts. The results illustrate that dynamic pre-positioning outperforms the other three strategies in cost savings. It also indicates that a higher return price is particularly helpful for decreasing unmet demand. The proposed models can help relief agencies evaluate and choose the solutions that will have the greatest overall effectiveness in the context of different relief practices.     

Some problems in actuarial finance involving sums of dependent risks

A trend in actuarial finance is to combine technical risk with interest risk. If Y_t , t = 1, 2, denotes the timevalue of money (discount factors at time t ) and X_t the stochastic payments to be made at time t , the random variable of interest is often the scalar product of these two random vectors V = X_t Y_t . The vectors X and Y are supposed to be independent, although in general they have dependent components. The current insurance practice based on the law of large numbers disregards the stochastic financial aspects of insurance. On the other hand, introduction of the variables Y ₁, Y ₂, to describe the financial aspects necessitates estimation or knowledge of their distribution function.
We investigate some statistical models for problems of insurance and finance, including Risk Based Capital/Value at Risk, Asset Liability Management, the distribution of annuities, cash flow evaluations (in the framework of pension funds, embedded value of a portfolio, Asian options) and provisions for claims incurred, but not reported (IBNR).     

Innovation problems and search for solutions in crowdsourcing platforms – A simulation approach

Crowdsourcing initiatives are increasingly spreading among organisations aiming at outsourcing the development of solutions to internal innovation problems to external problem solvers. However, while knowledge about crowdsourcing is growing, a complete understanding of the underlying dynamics of these initiatives is still lacking. This study aims at elucidating this topic by investigating the influence exerted by the interplay between the characteristics of innovation problems, individuals developing solutions (problem solvers), and crowdsourcing platforms on the related problem solving performance. Specifically, we use NK fitness landscapes to simulate the search for solutions conducted by problem solvers in several scenarios, depending on the decomposability and accuracy of delineation of the innovation problems, the degree of bounded rationality of the solvers, and the cooperation policies of the crowdsourcing platforms. Our findings contribute to the development of the theory on search for solutions in crowdsourcing initiatives, by revealing the characteristics of problem solvers and the types of platforms that maximise the performance of the problem solving process, as the quality of the best solution provided and the time required to elaborate on it, according to specific innovation problems. Furthermore, our findings promote the formulation of guidelines for organisations using crowdsourcing to solve their innovation problems, and for the crowdsourcing platforms’ managers.     

A minimal complete class theorem for decision problems where the parameter space contains only finitely many points

In this note we show that the class of stepwise Bayes procedures, suitable defined, forms the minimal complete class for decision problems where the parameter contains only finitely many points. Beyond the assumption on the parameter space, the result is quite general and extends some earlier results.Research supported in part by NSF grant DMS-8911548-01     

Breeding places for ethnic entrepreneurs: a comparative marketing approach

This paper aims to examine the performance conditions of ethnic (migrant) entrepreneurs in a modern economy. After a broad overview of key issues, an analytical tool from marketing theory is proposed, based on the five Ps (Product, Price, Place, Personnel and Promotion). Next, an empirical application is presented, in which results from an in-depth interview study on Moroccan entrepreneurs in Amsterdam are discussed. Given the linguistic and qualitative information in our data base, two recently developed pattern recognition methods for categorized information, namely Apriori and rough set methods, are deployed in order to derive meaningful association and classification rules that are helpful to identify conditional success or performance rules.     

A simple approach for the analysis of generalizea linear mixed models

A broad class of generalized linear mixed models, e.g. variance components models for binary data, percentages or count data, will be introduced by incorporating additional random effects into the linear predictor of a generalized linear model structure. Parameters are estimated by a combination of quasi-likelihood and iterated MINQUE (minimum norm quadratic unbiased estimation), the latter being numerically equivalent to REML (restricted, or residual, maximum likelihood). First, conditional upon the additional random effects, observations on a working variable and weights are derived by quasi-likelihood, using iteratively re-weighted least squares. Second, a linear mixed model is fitted to the working variable, employing the weights for the residual error terms, by iterated MINQUE. The latter may be regarded as a least squares procedure applied to squared and product terms of error contrasts derived from the working variable. No full distributional assumptions are needed for estimation. The model may be fitted with standardly available software for weighted regression and REML.     

Managing global projects: A structured approach for better performance

The purpose of this research effort is to develop a model for improving the performance of global projects using the underlying relations among the important enablers and barriers of global project performance. A number of factors are identified in the study, using a literature review to develop the model. A survey was used to determine the impact of these factors on global project performance. The model suggests different management practices for global projects versus traditional, co‐located projects. Different from the outcomes of traditional projects, research results suggest that leadership and establishing trust is a first step in the initial stages of the global project.     

城市要科学发展--当前城市发展值得注意的几个倾向问题

我国城市发展建设进入一个充满机遇和挑战的新阶段.城市化、生态城市、宜居城市、紧凑城市、旧城改建等成为热门话题.作者就城市发展中的几个倾向问题提出一些看法:城市化不等于大城市化;生态城市不等于森林城市;宜居城市不等于富人城市;紧凑城市不等于高层化城市;旧城改建不等于重建城市.     

Saddlepoint approximations for the sum of independent non‐identically distributed binomial random variables

We discuss saddlepoint approximations to the distribution of the sum of independent non‐identically distributed binomial random variables. We examine the accuracy of the saddlepoint methods for a sum of 10 binomials with different sets of parameter values. The numerical results indicate that the saddlepoint approximations provide very accurate estimates for the probability mass function and the right‐tail probabilities for the cumulative distribution function of the sum.     

A methodology proposal for collaborative business process elaboration using a model-driven approach

Business process management (BPM) principles are commonly used to improve processes within an organisation. But they can equally be applied to supporting the design of an Information System (IS). In a collaborative situation involving several partners, this type of BPM approach may be useful to support the design of a Mediation Information System (MIS), which would ensure interoperability between the partners’ ISs (which are assumed to be service oriented). To achieve this objective, the first main task is to build a collaborative business process cartography. The aim of this article is to present a method for bringing together collaborative information and elaborating collaborative business processes from the information gathered (by using a collaborative situation framework, an organisational model, an informational model, a functional model and a metamodel and by using model transformation rules).     

A time-varying copula approach for constructing a daily financial systemic stress index

This paper develops a financial systemic stress index (FSSI) for the US financial market. We propose a time-varying copula method to model the dependence structure among financial sectors in order to build a correlated financial stress model that can signal systemic financial risks. The copula method is preferable to the traditional approach, enabling the modeling of non-linear correlations. Our analyses show that the dependencies across banking, security, and forex markets are best modeled by Archimedian copulas. Finally, we conduct a Markov Switching Autoregressive (MS-AR) model for FSSI and identify high financial stress episodes taking place in 2008–2009, 2011 and 2020.     

A systems approach to the management of a hospital for short-term patients.

The endemic problems of health system management are reviewed, as is the difficulty of taking a systems viewpoint. It is argued, and demonstrated, that, by using some very simple ideas of system structure it is remarkably easy to draw up a diagram of system influences. Such a diagram is drawn for the case of psychiatric patients who recycle in the system. The diagram is analyzed from the point of view of its properties as a feedback control system, and it is shown that there are alternative, and probably more satisfactory, management practices. Suggestions are made for the practical implementation of such policies. Finally it is argued that influence diagrams may be useful as agenda for discussions, and that they offer advantages over conventional agenda.     

A class of flat prior distributions for the Poisson‐gamma hierarchical model

A wide class of prior distributions for the Poisson‐gamma hierarchical model is proposed. Prior distributions in this class carry vague information in the sense that their tails exhibit slow decay. Conditions for the propriety of the resulting posterior density are determined, as well as for the existence of posterior moments of the Poisson rate of either an observed or an unobserved unit.     

Reusing process fragments for fast service composition: a clustering-based approach

With the proliferation of Web services over the Internet and due to the increasing complexity of users’ needs, Web service composition has emerged as a powerful method of software reuse, allowing to deliver complete business processes as a set of interacting services. To guarantee a rapid and secure service composition, fragments of available business processes at different granularities may be considered as a composition unit and recombined to deliver effective compositions. Despite the benefits of this method, most of the existing works do not take into consideration the reuse of service process fragments (SPF). Reusing SPFs allows, not only to minimize the composition time, but also to improve the reliability of the composition process. In this paper, we propose a Web service composition approach that aims to combine service process fragments rather that atomic services. We adopt a powerful mathematical model called Formal Concept Analysis (FCA) to define the relationships between services and fragments. Moreover, we exploit the regrouping capabilities of FCA by proposing algorithms for the extraction of candidate fragments’ combinations. A scoring function is also defined to determine the quality level of each SPF and its ability to participate in a composition. The experimental studies proved the effectiveness of our FCA-based approach compared to existing state-of-the-art solutions.     

Who pays for whom? Elements of a macroeconomic approach to income inequality

National income is generated through national production in the form of ‘value added’; it is expended on goods and services in the form of ‘disposable’ or ‘net’ income. In this paper, I investigate what happens in between. The circuit of income flows generated in this way is comparable to the circuit of product flows, in its complexity. It can be analysed, so the tenet of the paper, in a similar way, by means of well-known tools of input–output (IO) analysis; this on the pre-condition, however, that you draw out the institutional framework of an economy in similar detail as is now customarily done for production units in IO analysis. Existing data do not suffice for the purpose, at present; this paper shows, by way of some exemplary calculations, what insight into the mechanism of national income distribution is gained if the necessary data, normally in the form of a large social accounting matrix, are provided.