Optimal tactics for close-support operations— III. Degraded intelligence and communications

A new generation of C³ (command, control, and communication) models for military cybernetics is developed. Recursive equations for the solution of the C³ problem are derived for an amphibious campaign with linear time-varying dynamics. Air and ground commanders are assumed to have no intelligence and no communications. Numerical results are given for the optimal decision rules.     

Optimal tactics for close support operations: Part IV,perfect intelligence and communications

A new generation ofC ³ (command, control, and communication) models for military cybernetics is developed. Recursive equations for the solution of theC ³ problem are derived for an amphibious campaign with linear, time-varying dynamics. Air and ground commanders are assumed to have perfect intelligence and perfect communications. Numerical results are given for the optimal decision rules.     

Bayesian decision making and military command and control

We discuss firstly the problem of military decision, in the context of the more general development of ideas in the representation of decision making. Within this context, we have considered a mathematical model—Bayesian Decision—of decision making and military command. Previous work has been extended, and applied to this problem. A distribution of belief in outcome, given that a decision is made, and a Loss function—a measure of the effect of this outcome relative to a goal—are formed. The Bayes' Decision is the decision which globally minimises the resultant bimodal (or worse) Expected Loss function. The set of all minimising decisions corresponds to the surface of an elementary Catastrophe. This allows smooth parameter changes to lead to a discontinuous change in the Bayes' decision. In future work this approach will be used to help develop a number of hypotheses concerning command processes and military headquarters structure. It will also be used to help capture such command and control processes in simulation modelling of future defence capability and force structure.     

Interactive Multi-Objective Programming: Its Aims,Applications and Demands

The past decade has seen a considerable development of techniques designed to help decision makers faced with problems involving conflicting objectives. In particular, a family of methods known collectively as interactive multi-objective programming has come to the fore. This paper presents the underlying rationale of such methods, albeit as seen by a devil's advocate, briefly surveys some areas of application, but then questions the validity of these methods because their assumptions are not supported by the empirical results of behavioural decision theory.     

A multi-objective multi-period stochastic programming model for public debt management

While raising debt on behalf of the government, public debt managers need to consider several possibly conflicting objectives and have to find an appropriate combination for government debt taking into account the uncertainty with regard to the future state of the economy. In this paper, we explicitly consider the underlying uncertainties with a complex multi-period stochastic programming model that captures the trade-offs between the objectives. The model is designed to aid the decision makers in formulating the debt issuance strategy. We apply an interactive procedure that guides the issuer to identify good strategies and demonstrate this approach for the public debt management problem of Turkey.     

A multiple criteria decision making approach to manure management systems in the Netherlands

The intensification of livestock operations in the last few decades has resulted in an increased social concern over the environmental impacts of livestock operations and thus making appropriate manure management decisions increasingly important. A socially acceptable manure management system that simultaneously achieves the pressing environmental objectives while balancing the socio-economic welfare of farmers and society at large is needed. Manure management decisions involve a number of decision makers with different and conflicting views of what is acceptable in the context of sustainable development. This paper developed a decision-making tool based on a multiple criteria decision making (MCDM) approach to address the manure management problems in the Netherlands. This paper has demonstrated the application of compromise programming and goal programming to evaluate key trade-offs between socio-economic benefits and environmental sustainability of manure management systems while taking decision makers’ conflicting views of the different criteria into account. The proposed methodology is a useful tool in assisting decision makers and policy makers in designing policies that enhance the introduction of economically, socially and environmentally sustainable manure management systems.     

应用灰色评价理论选择最优军事运输方式研究

在分析影响军事运输方式选择因素的基础上,依据层次分析法和灰色评价理论,建立了一种根据不同用户偏好的最优军事运输方式选择模型,这就为研制军事交通运输决策支持系统,进而实现军事交通运输指挥自动化奠定了基础.     

Optimal tactics for close support operations: Part I,degraded communications

A formidable problem in the mathematical studies of C³ (command, control, and communication) is the determination of the optimal decision rules for force commitments to be employed by headquarters. Recursive equations are derived for an amphibious campaign with time-invariant linear dynamics and quadratic costs. Air and ground commanders are assumed to have perfect intelligence with degraded communication between them.The authors have benefitted greatly from discussions with Colonels R. Geesey, C. Albo, and R. Reeves, USAF.     

Envisioning uncertainty in geospatial information

Geospatial reasoning has been an essential aspect of military planning since the invention of cartography. Although maps have always been a focal point for developing situational awareness, the dawning era of network-centric operations brings the promise of unprecedented battlefield advantage due to improved geospatial situational awareness. Geographic information systems (GIS) and GIS-based decision support systems are ubiquitous within current military forces, as well as civil and humanitarian organizations. Understanding the quality of geospatial data is essential to using it intelligently. A systematic approach to data quality requires: estimating and describing the quality of data as they are collected; recording the data quality as metadata; propagating uncertainty through models for data processing; exploiting uncertainty appropriately in decision support tools; and communicating to the user the uncertainty in the final product. There are shortcomings in the state-of-the-practice in GIS applications in dealing with uncertainty. No single point solution can fully address the problem. Rather, a system-wide approach is necessary. Bayesian reasoning provides a principled and coherent framework for representing knowledge about data quality, drawing inferences from data of varying quality, and assessing the impact of data quality on modeled effects. Use of a Bayesian approach also drives a requirement for appropriate probabilistic information in geospatial data quality metadata. This paper describes our research on data quality for military applications of geospatial reasoning, and describes model views appropriate for model builders, analysts, and end users.     

Measuring consensus in decision making: an application to maritime command and control

An important component of maritime command and control is the information that has value to Royal Navy commanders in making campaign decisions. Studies aimed at identifying information requirements generally do so in a wargame context with several test subjects assuming command roles. An important adjunct to this work then is the assessment of how closely the subjects agree that the proposed information set is indeed valuable. In this paper, we focus on assessing the degree to which the test subjects participating in a MoD sponsored maritime command and control study agreed to a proposed set of information elements deemed valuable to taking combat decisions. The methodology involves the simulation of naval combat. The participants (former Royal Navy Captains and Admirals) are asked to choose a course of action that best accomplishes a stated mission. Information is provided on request. Each pair of participants is characterized by its set of information requirements. The objectives are (1) to define an overall information set that minimizes disagreement among the participants in some way; and (2) to develop a metric that assesses the amount of disagreement among the participants. Two metrics are presented: a mean consensus and a median consensus.     

基于模糊需求的多产品供应商选择的多目标规划模型

由决策于环境的不确定性,供应商选择问题存在大量的模糊信息,传统的确定性规划模型已经不能够很好地处理此类问题。本文基于模糊需求量信息,对于多产品供应商问题建立了模糊多目标规划模型。同时考虑到各目标及约束的重要性程度不同的影响,通过引进适当的权重对多目标规划模型进行求解。文中结合实际算例验证模型的可行性和有效性。     

Optimal tactics for close support operations: Part VI,summary of numerical results

A new generation of C³ (command, control, and communication) models for military cybernetics has been developed in recent papers. Recursive equations for the solution of the C³-problem have been derived for an amphibious campaign with linear time-varying dynamics. Air and ground commanders are assumed to have different modes of intelligence and communications. Numerical results are summarized, and the relative importance of intelligence and communications is discussed.     

基于区间数确定性与不确定性相互作用点的多属性决策

区间数多属性决策中的区间数是确定性与不确定性的对立统一体,存在着相互依赖、相互作用的关系,利用集对分析的联系数理论可以计算出一个区间数的确定性与不确定性的"相互作用点",以此反映一个区间数确定性与不确定性相互作用的大小,该点同时可以作为该区间数的"代表点"参与决策,从而使区间数多属性决策过程简明,快捷.     

Optimal tactics for close support operations. II. Degraded communications with linear time-varying dynamics

The optimal decision rules for force commitments are obtained in mathematical studies of C³ (command, control, and communication). Recursive equations for the solution of the C³ problem are derived for a perturbation model with linear time-varying dynamics. Air and ground commanders are assumed to have perfect intelligence with degraded communication between them. Numerical results are given for several amphibious assaults.     

An adjustable approach to intuitionistic fuzzy soft sets based decision making

Molodtsov initiated the concept of soft set theory, which can be used as a generic mathematical tool for dealing with uncertainty. There has been some progress concerning practical applications of soft set theory, especially the use of soft sets in decision making. In this paper we generalize the adjustable approach to fuzzy soft sets based decision making. Concretely, we present an adjustable approach to intuitionistic fuzzy soft sets based decision making by using level soft sets of intuitionistic fuzzy soft sets and give some illustrative examples. The properties of level soft sets are presented and discussed. Moreover, we also introduce the weighted intuitionistic fuzzy soft sets and investigate its application to decision making.     

A rough set approach to intuitionistic fuzzy soft set based decision making

The soft set theory, originally proposed by Molodtsov, can be used as a general mathematical tool for dealing with uncertainty. Since its appearance, there has been some progress concerning practical applications of soft set theory, especially the use of soft sets in decision making. The intuitionistic fuzzy soft set is a combination of an intuitionistic fuzzy set and a soft set. The rough set theory is a powerful tool for dealing with uncertainty, granuality and incompleteness of knowledge in information systems. Using rough set theory, this paper proposes a novel approach to intuitionistic fuzzy soft set based decision making problems. Firstly, by employing an intuitionistic fuzzy relation and a threshold value pair, we define a new rough set model and examine some fundamental properties of this rough set model. Then the concepts of approximate precision and rough degree are given and some basic properties are discussed. Furthermore, we investigate the relationship between intuitionistic fuzzy soft sets and intuitionistic fuzzy relations and present a rough set approach to intuitionistic fuzzy soft set based decision making. Finally, an illustrative example is employed to show the validity of this rough set approach in intuitionistic fuzzy soft set based decision making problems.     

Model choice in multicriteria decision aid

The purpose of this paper is to illustrate, using a real case study, one of the points stressed in the “Manifesto of the new Multi Criteria Decision Aid (MCDA) era” (Bouyssou et al., 1993) regarding the application of the basic theory of MCDA procedures. Although the great diversity of MCDA procedures may be seen as a strong point, it can be a weakness, and a systematic analysis of decision procedures if one method makes more sense than another for a specific problem is necessary. The problem of selecting the most appropriate (MCDA) technique for a particular application is in itself a MCDA problem since the decision making criteria used for the selection are different and conflicting in nature. In this paper three selection models are implemented to assist the system analyst, when confronted with a multi-objective decision problem, to select the most appropriate MCDA technique for application to the problem of optimal ranking of water development projects in an arid country. These models are developed by Deason (1984), Gershon (1981), and Tecle (1988). Results indicated that PROMETHEE was the most preferred method for this problem.     

基于D-S证据理论的群决策专家意见集结方法

将D-S证据理论应用于群决策，指出其优势在于应用基本可信度分配函数描述专家意见，并能区分对所描述对象不知道和否定的差异。在专家意见集结上，Dempster证据合成规则有一定的局限性，当证据发生冲突时，会得到不合理的结果。定义了证据间的分歧度，提出一种专家意见集结方法，使得专家意见发生冲突时亦可得到合理的集结结果。     

A survey of quantum-like approaches to decision making and cognition

There has always been a steady interest in how humans make decisions amongst researchers from various fields. Based on this interest, many approaches such as rational choice theory or expected utility hypothesis have been proposed. Although these approaches provide a suitable ground for modeling the decision making process of humans, they are unable to explain the corresponding irrationalities and existing paradoxes and fallacies. Recently, a new formulation of decision theory that can correctly describe these paradoxes and possibly provide a unified and general theory of decision making has been proposed. This new formulation is founded based on the application of the mathematical structure of quantum theory to the fields of human decision making and cognition. It is shown that by applying these quantum-like models, one can better describe the uncertainty, ambiguity, emotions and risks involved in the human decision making process. Even in computational environments, an agent that follows the correct patterns of human decision making will have a better functionality in performing its role as a proxy for a real user. In this paper, we present a comprehensive survey of the researches and the corresponding recent developments. Finally, the benefits of leveraging the quantum-like modeling approaches in computational domains and the existing challenges and limitations currently facing the field are discussed.