A multiobjective integer programming model for the land acquisition problem

The purpose of this paper is to present a multiobjective integer programming formulation for the analysis of the land acquisition problem. There are two important contributions of this paper. First, the model incorporates the discrete and multiobjective nature of land acquisition. Second, we present an efficient, specialized algorithm for finding non-inferior solutions of a multiobjective integer program, a problem for which a general-purpose algorithm, applicable to moderately sized problems, does not exist.     

A survey and critique of multiobjective power plant siting decision rules

This paper reviews the use of multiobjective decision rules for solving power plant siting problems. After a discussion of exclusionary site screening methods for bounding the decision space, classes of multiobjective and goal programming desicion rules are discussedin the context of final site selection. Advances and limitations of these methods are highlighted. Although multiobjective decision rules have seen numerous applications to power plant siting in the literature, few electric utility companies have used these methods in practice. A review of the use of multiobjective methods in actual power plant siting decisions is also presented, and reasons for the paucity of real-world applications are suggested.     

An approach to the display and analysis of multiobjective problems

In all operations research applications, the problem of implementation rests on the information conveyed to the decision maker. The presentation of results is a critical link in the success of a project. An ineffective transfer of information will reduce the chance of decision maker acceptance. This final step in the analysis is particularly difficult in multiobjective analyses, where the amount of relevent information increases with each performance measure.This paper will describe an alternative to the typical graphical approach to multiobjective display, which is adaptable to any number of objectives. A real world example is given and some theoretical insights are developed.     

USING A CGE MODEL TO IDENTIFY THE POLICY TRADE-OFF BETWEEN UNEMPLOYMENT AND INFLATION. THE EFFICIENT PHILLIPS CURVE

This paper provides a new reading of a classical economic relation: the short-run Phillips curve. Our point is that, when dealing with inflation and unemployment, policy-making can be understood as a multicriteria decision-making problem. Hence, we use so-called multiobjective programming in connection with a computable general equilibrium (CGE) model to determine the combinations of policy instruments that provide efficient combinations of inflation and unemployment. This approach results in an alternative version of the Phillips curve labelled as efficient Phillips curve. Our aim is to present an application of CGE models to a new area of research that can be especially useful when addressing policy exercises with real data. We apply our methodological proposal within a particular regional economy, Andalusia, in the south of Spain. This tool can give some keys for policy advice and policy implementation in the fight against unemployment and inflation.     

Institutionalism versus Orthodoxy

A bstract . Orthodox economics has been quite effective in exploiting equilibrium methodology; equilibrium as a heuristic device, as a theoretical norm, and as a prototype of the scientific method. Also, orthodoxy has contrived the dichotomy of equilibrium-anti-equilibrium to depict institutional thought as being muddled and unscientific. Institutionalists have not successfully countered these attacks, nor have they adequately articulated a comprehensive methodological alternative to orthodoxy. Institutionalists have paid too much attention to the methodological components of institutionalism and have neglected the articulation of a guiding, overall methodology. It is proposed that institutionalists recast the methodological debate by expanding the arena from equilibrium-anti-equilibrium analysis to the broader context of closed versus open systems analysis. This would both help expose the methodological weaknesses of orthodox economics, and demonstrate the relevance and power of institutionalism for socioeconomic investigation.     

A multiobjective optimization model for project selection with probabilistic considerations

When faced with limited resources, project managers must determine which projects to fund at what levels from a pool of potential ones. This problem of project selection is inherently multiobjective since various factors, such as the available budget, the chance of success, and the efficient allocation of the project team, must be considered simultaneously. The uncertainty of the data at the time decisions are made further complicates project selection. In this paper, a multiobjective, integer-constrained optimization model with competing objectives for project selection is formulated using probability distributions to describe costs. The objectives correspond to important project criteria, such as: rank (value), managerial labor needed, and average cost. The subjective rank is determined via the Analytic Hierarchy Process. The model is applied to a data set from a US government agency that involves 84 separate projects. The results indicate improved budgetary efficiency compared to the actual project selection, thus supporting use of the model for public sector project selection. The model is unique since it integrates multiobjective optimization, Monte Carlo simulation, and the Analytic Hierarchy Process.     

The Pervasiveness And Trajectory Of Methodological Choices: A 20‐Year Review Of Human Resource Management Research

This article examines the methodological choices of researchers studying the HR practices–outcome relationship via a content analysis of 281 studies published across the past 20 years. The prevalence and trajectory of change over time are reported for a wide range of methodological choices relevant to internal, external, construct, and statistical conclusion validity. While the results indicate a high incidence of potentially problematic cross‐sectional, single‐informant, and single‐level designs, they also reveal significant improvements over time across many validity relevant methodological choices. This broad‐based improvement in the methodological underpinnings of HR research suggests that researchers and practitioners can view the findings reported in the HR literature with increasing confidence. Directions for future research are provided. © 2016 Wiley Periodicals, Inc.     

A multiobjective optimization approach to smart growth in land development

In this paper we apply a multiobjective optimization model of Smart Growth to land development. The term Smart Growth is meant to describe development strategies—that do not promote urban sprawl. However, the term is somewhat open to interpretation. The multiobjective aspects arise when considering the conflicting interests of the various stakeholders involved in land development decisions: the government planner, the environmentalist, the conservationist, and the land developer. We present a formulation—employing linear and convex quadratic objective functions subject to polyhedral and binary constraints for the stakeholders. The resulting optimization problems are convex, quadratic mixed integer programs that are NP-complete. We report numerical results with this model for Montgomery County, Maryland, and present them using a geographic information system (GIS).     

The Case of Case Studies: On the Methodological Discussion in Comparative Political Science

A look at comparative political science shows that many contributions to the field do compare, but do not reflect the methods used. This paper discusses the analytical differences between the comparative method, the statistical method and experiment. An overview of the methodological discussion shows that a case study and namely the analysis of deviant cases has its place in comparative analysis. The last part of this paper consequently deals with different forms of case study analysis and the underlying research interest. The discussion emphasizes that in-depth analyses of a limited number of cases is the core of comparative political science with a good ratio between methodological input and analytical results.     

Logit and multinomial logit models for discrete-time event-history analysis: a causal analysis of interdependent discretestate processes

This paper introduces a new direction of methodological elaborations in event-history analysis based on discrete-time logit and multinomial logit models. The methodological elaborations address (1) simultaneous analysis of two-way transitions between two states, and (2) its extension for a causal analysis of two interdependent two-state processes. The former elaboration permits a more parsimonious and unambiguous expression for the effects of covariates on the dependent process than can be obtained by separate analyses of each direction of transition. The latter elaboration provides an extension for a log-linear causal analysis of 16-fold tables presenting two-wave-two-variable panel data, and relates the log-linear analysis to event-history analysis. An illustrative application, focusing on the dynamic relationship between premarital cohabitation and marijuana use, demonstrates the usefulness of the new models and methods.     

Models for conflict resolution in ecosystem management

Tools developed in the fields of decision analysis and game theory that have potential for use in public sector conflict resolution are reviewed. The strengths and weaknesses, as well as the axioms defining principles of fairness, are examined for multiobjective optimization, Nash and Nash–Harsanyi solutions, voting models, and the Shapley value. The case of conflict between stakeholders over proposed oil and gas leasing on National Forest System lands is presented as a sample application. We conclude that the Shapley value is the appropriate approach for determining the “fairness” of alternative conflict solutions, at least in those situations where cardinal utilities can be estimated.     

Content analytic approach to measuring constructs in operations and supply chain management

This paper presents and illustrates the content analytic approach to measuring constructs in operations and supply chain management (OSCM). In this paper, a methodological review of OSCM empirical research in 2002-2007 is provided to highlight that OSCM empirical studies, unlike those in other business disciplines, have rarely used content analysis as a methodological tool. This paper then reviews the methodological strengths of content analysis, which lie primarily in its malleability, economy of data collection, repeatability, and unobtrusiveness. These strengths not only make content analysis a viable empirical method but also position it as a method that can be used in concert with other empirical methods in OSCM research, such as survey, case study, and secondary research methodologies. This paper also proposes a generic framework for a content analytic approach to measuring theoretical constructs, illustrates the application of the framework to a construct in the OSCM literature (buyer-supplier relationalism), and reports the satisfactory results of reliability and validity tests for the content analysis-based measure of buyer-supplier relationalism. In addition, this paper proposes and demonstrates that the use of convergence study in tandem with content analysis can substantially reduce the content analysis efforts needed in measuring the construct of interest, thus improving the overall efficiency of the process of content analysis.     

基于协PSO算法的物流配送中心选址研究

针对多目标物流配送中心选址问题,建立选址模型,并设计离散协粒子群算法,最后利用该算法进行了实例研究,结果表明该算法是有效、可行的。     

Conducting multilevel studies in purchasing and supply management research

Purchasing and supply management (PSM) research commonly covers multiple levels of theory and analysis. The theorizing and simultaneous testing of hypotheses across multiple levels is referred to as multilevel analysis (MLA) and is commonly performed using hierarchical linear modeling (HLM). Researchers in the PSM domain have paid little attention thus far to the topic of multilevel studies. Although MLA holds the potential to yield novel insights into PSM issues, it also generates new challenges for authors and reviewers alike. We contribute to this methodological dialogue by examining reasons for conducting multilevel PSM research and offering practical guidance for increasing its methodological rigor.     

A multiobjective modeling approach to locating incinerators

The location of hazardous material incineration facilities is an important problem due to the environmental, social, and economic impacts that they impose. The costs associated with the facilities and the risks placed on nearby populations are important concerns as are the distributions of these costs and risks. This paper introduces a mixed-integer, multiobjective programming approach to identify the locations and capacities of such facilities. The approach incorporates a Gaussian dispersion model and a multiobjective optimization model in a GIS-based interactive decision support system that planners can access via the Internet. The proposed approach is demonstrated via a case study in central Portugal where the national government has decided to locate a large facility for the incineration of hazardous industrial waste. Due to intense local and national opposition, construction of the facility has been delayed. The system has been designed so that it can be used by decision makers with no special training in dispersion modeling, multiobjective programming, or GIS.     

A supplementary note to Questionnaire Sorting and Fuzzy Sorting

This note supplements the article “An exploration of Questionnaire Sorting and Fuzzy Sorting” (this volume). It relates to recent methodological improvements by Capra (2005), who introduced a factor analysis solution to cover set cluster analysis.     

Methods for analyzing decision-making: a framework approach

In political science an eternal question concerns how decisions and policies arise. Modern society, characterized by more uncertainty and complexity than before, increases the challenge of providing valid answers. However, the general lack of methodological concern in several previous studies in this area stresses the need for elaborations of more suitable approaches. In this article we add a methodological perspective that deals with this very question. By reviewing and analyzing earlier research on how decision-making is reached, the overall ambition of this article is to create a framework that can lay the methodological foundation for further studies. Such a framework, which takes into account both the complexity of modern multi-governance societies and adds methodological perspectives of macro and micro standpoints as well as of causal mechanisms, can be used in future research to achieve richer pictures of how decision-making is carried out. In addition, we show how a certain technique of analysis is highly compatible to this framework and that jointly these features provide solutions for a better understanding of the complexity of modern decision-making. All in all, applying this strategy can be used to better systematize complex causal chains that reflect different analytical levels and thereby increase leverage on how to understand and explain the process of political decisions.     

A common base for quality control criteria in quantitative and qualitative research

In the social sciences, several scientific paradigms are mutually isolated owing to their use of specific sets of methodological criteria and quality control procedures. In this article, the central hypothesis, to be tested by conceptual analysis and logical reasoning, is that recommended procedures for quality control in quantitative as well as qualitative research can be derived from a common base of regulative ideas. By ‘qualitative’, we mean the complex of ethnographic, anthropological, symbolic interactionist, ethnoscience and related approaches. A second goal is to demonstrate the use of regulative ideas as a parsimonious and fruitful base for a comparative analysis of methodological canons. Although our focus is on the comparison of quantitative and qualitative (or: naturalistic) research, we also pay attention to policy research as opposed to fundamental research.     

网络计划多目标优化问题的研究

对网络计划多目标优化的问题进行了探讨，在工期一费用优化分析的基础上，建立了工期、费用、工程质量、完工概率及资源均衡等多目标综合优化的模型，试图在整体上解决网络计划的优化问题。     

基于层次关联矩阵法的国际工程项目投标决策研究

在分析了工程承包企业投标决策的影响因素的基础上,总结了国内外在投资决策方面的相关研究成果和局限性。针对国际工程项目的特点,建立了项目方案评价指标体系。通过将层次分析法和关联矩阵法两者结合,提出了层次关联矩阵法来对工程项目进行投标决策,并通过将该方法应用于具体的案例来检验了方法的有效性。