Optimal Decision Model Research Articles

Specialization and Cooperation in Research

An optimal decision model is developed to explore the impact of the structure of knowledge on specialization and cooperation in research. It shows that, (1) the degree of specialization in knowledge increases with the depth of knowledge and cooperation efficiency, and decreases with the average number of disciplines that are required for the solution of the problem; (2) the problem which requires the knowledge of more disciplines is likely to be solved by more cooperative researchers. Conclusion (2) and part of conclusion (1) are tested by empirical evidence in economic study, where the sample comes from the papers published in the Journal of Political Economy.

Health state evaluation of an item: A general framework and graphical representation

This paper presents a general theoretical framework to evaluate the health state of an item based on condition monitoring information. The item's health state is defined in terms of its relative health level and overall health level. The former is evaluated based on the relative magnitude of the composite covariate and the latter is evaluated using a fractile life of the residual life distribution at the decision instant. In addition, a method is developed to graphically represent the degradation model, failure threshold model, and the observation history of the composite covariate. As a result, the health state of the monitored item can be intuitively presented and the evaluated result can be subsequently used in a condition-based maintenance optimization decision model, which is amenable to computer modeling. A numerical example is included to illustrate the proposed approach and its appropriateness.

Soil organic carbon changes in dynamic land use decision models

Soil organic carbon can be sequestered through various land management options depending on the soil organic carbon status at the beginning of a management period. This initial soil organic carbon status results from a certain soil management history in a certain soil climate regime. Similarly, the prediction of future carbon storage depends on the time path of future soil management. Unfortunately, the number of possible management trajectories reaches non-computable levels so fast that explicit representations of future management trajectories are infeasible for most existing empirical land use decision models. Not surprisingly, the impact of different management trajectories has been ignored. This article proposes a computationally feasible mathematical programming method for integration of soil state dependent sequestration rates in dynamic land use decision optimization models. The possible soil organic carbon range is divided in several adjacent carbon states. For each soil management practice, location, and initial soil organic carbon state, transition probabilities of moving into a different or remaining in the same state are computed. Subsequently, these probabilities are used in dynamic equations to update the soil organic carbon level before and after each period. To illustrate the impacts of this Markov chain based method, a case study portraying Australian wheat farmers is conducted.

Likelihood ratio, optimal decision rules, and correct response probabilities in a signal detection theoretic, equal-variance Gaussian model of the observer in the 4IAX paradigm

This article provides a synthetic account of the likelihood ratio, optimal decision rules, and correct response probabilities in a signal detection theoretic model of the observer in the dual-pair comparison, or four-interval AX (4IAX), paradigm. The model assumes a static sampling process, resulting in four, equal-variance normally distributed (i.e., Gaussian) observations on each trial First, a likelihood ratio equation allowing for an arbitrary degree of correlation between observations is provided. Specific solutions for the cases of independent and highly correlated observations are then derived. It is shown that these solutions, and the associated decision rules, correspond to those provided independently in earlier publications. A modified 4IAX paradigm involving, as a standard, an additional stimulus (C) located medially between the A and the B stimuli is also considered. It is shown that the optimal (static, equal-variance, Gaussian) decision model for this paradigm is unaffected by correlation between observations and is equivalent to the standard 4IAX with highly correlated observations. Finally, we consider how, under the considered (static, equal-variance, Gaussian) model, the proportion of correct responses in the different versions of the 4IAX paradigm is related to d', and a solution for the case of independent observations is provided.

상수관망의 구역별 최적개량 의사결정 시스템의 개발

본 연구에서는 노후관망의 최적개량 계획수립을 위한 의사결정모형을 개발하였다. 각각의 관거에 대한 개량계획을 수립하는 기존에 개발된 다른 모형과 달리 노후화된 상수관망을 소구역으로 구분하여 각 소구역의 개량계획을 수립하였다. 개발된 모형에서는 최적개량 의사결정을 위해 개량비용(교체비용, 갱생비용, 유지보수비용), 개선이익(펌프운영비 감소이익, 누수 감소이익) 및 수리학적 타당성을 고려하였다. 화음탐색법을 최적화기법으로 적용하였으며 수리학적 타당성 검토를 위해 수리해석 모형인 EPANET을 연계하였다. 대구시의 실제 상수도관망에 개발된 모형을 적용하였으며, 매설기간과 관의 종류에 의존하는 기존 방법과 달리 관의 내구성, 통수능, 비용 등을 고려하는 최적개량의사결정 시스템으로 활용될 수 있음을 확인하였다. The purpose of this study is to develop an optimal, long-term planning model for improvement of water distribution networks. The water distribution system is divided into sub-zones and the decision of improvement plan is made for each sub-zone. Costs for replacement, rehabilitation and repair, benefits including reduced pumping and leakage costs, and hydraulic reliability are considered to make optimal decision for improvement planning of water network. Harmony search algorithm is applied to optimize the system and hydraulic analysis model EPANET is interfaced with the optimal decision model to check the hydraulic reliability, The developed model is applied to actual water distribution system in Daegu-city, South Korea. The new model which use durability, conveyance and cost as a decision variable is different from existing methods which use only burying period and pipe type and can be used as optimal decision making system for water distribution network.

The Hyperbolic Forest Owner

This paper examines the implications of quasi-hyperbolic inter-temporal preferences to the Faustman model. The use of decreasing discount rates leads to dynamically inconsistent behavior. To solve this problem a two-stages optimization decision model is developed. The resulting actual cutting time will be anticipated compared to the Faustman optimal cutting time. If, alternatively, the equivalent constant rate of discount is the empirically observed discount rate, then the optimal cutting time is the same, but the present value of profits for the hyperbolic forest owner is always higher than the one resulting from the equivalent constant discount rate. All these results apply to both the single and the multiple rotation problems.

Optimal decision-making model of spatial sampling for survey of China’s land with remotely sensed data

In the remote sensing survey of the country land, cost and accuracy are a pair of conflicts, for which spatial sampling is a preferable solution with the aim of an optimal balance between economic input and accuracy of results, or in other words, acquirement of higher ac-curacy at less cost. Counter to drawbacks of previous application models, e.g. lack of compre-hensive and quantitative-comparison, the optimal decision-making model of spatial sampling is proposed. This model first acquires the possible accuracy-cost diagrams of multiple schemes through initial spatial exploration, then regresses them and standardizes them into a unified ref-erence frame, and finally produces the relatively optimal sampling scheme by using the discrete decision-making function (built by this paper) and comparing them in combination with the dia-grams. According to the test result in the survey of the arable land using remotely sensed data, the Sandwich model, while applied in the survey of the thin-feature and cultivated land areas with aerial photos, can better realize the goal of the best balance between investment and accuracy. With this case and other cases, it is shown that the optimal decision-making model of spatial sampling is a good choice in the survey of the farm areas using remote sensing, with its distin-guished benefit of higher precision at less cost or vice versa. In order to extensively apply the model in the surveys of natural resources, including arable farm areas, this paper proposes the prototype of development using the component technology, that could considerably improve the analysis efficiency by insetting program components within the software environment of GIS and RS.

Solving linear optimization problem with fuzzy relational equations as constraints

Implementation of fuzzy relation equations (FREs) as constraints in a linear optimization model for decision making problems is the central concept of the present paper. Due to non-convex nature of the solution set of FREs, it (the solution set) is characterized as lattice and a feasible domain of the optimization model has been obtained. The objective function of linear model has been characterized over the feasible domain. An algorithm to compute all the minimal solutions is obtained. A basic algorithm is also presented to find optimal solution of the problem and has been illustrated through a constructed example.

Determination of AGC capacity requirement and dispatch considering performance penalties

A continuous and near instantaneous balance between generation supply and load demand must be maintained in power system operation. As a kind of regulation reserve, automatic generation control (AGC) is widely employed for maintaining system security and reliability, especially for controlling frequency deviation and supporting commercial transactions. In a competitive electricity market, AGC services are either contracted via negotiations between the market operator and generation companies concerned, or procured via a certain form of auction. A new framework to determine AGC capacity requirement and to deal with regulation dispatch under uncertain demand in a competitive electricity market is presented in this paper. First, the stochastic characteristics of AGC capacity requirement and services are analyzed. A stochastic optimization decision-making model for determining optimal AGC capacity requirement is then developed, followed by a pricing analysis which reveals that a trade-off between economic efficiency and system security must be made by the market operator. Finally, an optimal AGC dispatch algorithm is suggested. A numerical study is given to further demonstrate the essential features of the proposed model and method.

Understanding User Decision Making and the Value of Improved Precipitation Forecasts: Lessons From a Case Study

A case study of the impact of improved precipitation forecasts on the snow-fighting operations of the New York State Thruway is reported. The goal was to use currently available data and literature on forecast process, communication, and use in conjunction with observations and interviews with key decision makers to derive a model that yields estimates of value to users based on a model of their decision processes rather than an optimal decision-making model. That goal proved too ambitious due to limitations in available data. A major lesson learned from this research is the importance of improved, ongoing data collection to support studies of use and value of weather information. A more holistic approach to understanding and realizing forecast value is needed, that is, one in which information (both of forecast skill and usage) centered on the decision process is collected in a much more intensive manner than is presently the case.

The Impact of Need Frequency on Service Marketing Strategy

Strategic marketing decisions for services are complicated by factors that distinguish services from goods. Because services are intangible, variable, and the production and consumption experiences are inseparable, trial of the identical service to be purchased cannot be offered. Services cannot be inventoried, so potential customers are lost if they are unaware of a particular service or it is unavailable during their time of need. Partially due to the difficulty of matching service supply to demand, service marketers typically assume that it is best to work toward retaining current clients, rather than focusing too much on attracting new customers. If there is an ongoing or frequent periodic need for the service, it may indeed be less expensive to maintain an existing customer relationship than to build a new one; however, for services that customers require infrequently, the marketer must find ways to build awareness and attract new customers. Just as marketing strategies for manufactured goods depend on whether the items are frequently purchased or durable, more effective service marketing decisions may be obtained by considering whether customer needs are frequent or not. We discuss these differences in general terms, then provide an application, developing an optimal promotion strategy decision model for an infrequently purchased service. We conclude that customers in the market for infrequently purchased services have particularly high needs for product awareness and purchase risk reduction, influencing strategic marketing decisions.

Research on performance-based seismic design criteria

The seismic design criterion adopted in the existing seismic design codes is reviewed. It is pointed out that the presently used seismic design criterion is not satisfied with the requirements of nowadays social and economic development. A new performance-based seismic design criterion that is composed of three components is presented in this paper. It can not only effectively control the economic losses and casualty, but also ensure the building’s function in proper operation during earthquakes. The three components are: classification of seismic design for buildings, determination of seismic design intensity and/or seismic design ground motion for controlling seismic economic losses and casualties, and determination of the importance factors in terms of service periods of buildings. For controlling the seismic human losses, the idea of socially acceptable casualty level is presented and the ‘Optimal Economic Decision Model’ and ‘Optimal Safe Decision Model’ are established. Finally, a new method is recommended for calculating the importance factors of structures by adjusting structures service period on the base of more important structure with longer service period than the conventional ones. Therefore, the more important structure with longer service periods will be designed for higher seismic loads, in case the exceedance probability of seismic hazard in different service period is same.

Single price system model for optimal decisions in capital equipment purchasing

Capital equipment purchasing models require the consideration of several important factors that include both financial and non-financial measures. The traditional methods utilized for capital equipment purchasing decisions primarily consider cost-related factors and do not allow for the incorporation of other important measures that characterize the benefits derived from these systems. While the application of multifactor models and advanced mathematical programming techniques has received significant attention in this area, several of these existing methods also have limitations. The paper presents the application of a recently developed multicriteria technique referred to as the single price system model for optimal decisions in capital equipment purchasing. The technique has several distinct advantages over existing methods. The model application is demonstrated through a previously published dataset of flexible manufacturing technologies. The results provide interesting insights relating to negotiating and purchasing manufacturing technologies.

Optimal decision for the target value of performance-based structural system reliability

The optimal decision model of the target value of performance-based structural system reliability is established according to the cost-effectiveness criterion in the present paper. Three types of optimal decision models are studied: the conceptive model, the parameter programming model and the constraint relaxation model. The conceptive model is inoperable because the objective function must be expressed as the function of the structural target reliability. The parameter programming and constraint relax models are proved to be equivalent with Kuhn–Tucker conditions when the performance-based structural system reliability constraints are all active. Finally the numerical examples of RC-frames for different earthquake-resistant performance are calculated.

A decision optimization model for condition‐based maintenance

Notes earlier work which commented on the formation of a research group to develop condition‐based maintenance (CBM) decision models and associated software. This paper provides an update on the research direction that has been taken since 1995. In particular, the structure of software for CBM decision making is highlighted, along with possible future research directions.

Optimal decision of price and stock level in consideration of the influence for demand

We consider an optimal decision model of price and stock level in consideration of the influence for demand. Detailed optimal policies are obtained in the cases of both a linear demand function and a constant price elasticity of demand. Furthermore the solving method is shown in the case of random demand.

An optimization model for air pollution control decision making

There are several different control techniques that can be applied to control air pollution emissions. In this paper, a mixed integer linear program that determines the best selection strategy is illustrated. The objective of the program is to minimize the total control cost consisting of operating and investment costs. Various constraints are imposed on the model including a prescribed pollution reduction level and maximum budget available for investment. The model gives the optimum set of control options along with their optimum set-up times. The use of the model in pollution control decision making is illustrated using a representative case study.

PRODUCTION LOANS

In this paper, agency problems between stockholders and debtholders are considered in a simple model of the firm's optimal production decision. It is shown that in the presence of debt financing other than a production loan, the firm is motivated to underproduce, an agency problem analogous to Myers' classic underinvestment problem. If a production loan is employed in lieu of these other forms of debt, the underproduction problem is rectified.

A mechanism for reducing small-business customer waiting-line dissatisfaction

This paper presents a technique whereby a small business (i.e. a one-cash register operation) can reduce customer waiting-line time dissatisfaction in the purchase stage of the consumer decision process. When the queue length reaches or exceeds critical value N*, another employee is temporarily transferred to the role of ‘server assistant’ to increase the effective service rate; when the queue length eventually decreases to a second critical value N*, the server assistant returns to primary duties. An optimal customer-reneging decision model is utilized to model the reneging character of the queue. Simulation experiments confirm key hypotheses concerning the behaviour of the queue and compare the effectiveness of a computed (N*, N*) policy with that of alternatives.

Mathematical Programming: Optimization Models for Business and Management Decision Making.

This text focuses on a particular group of management science models, known collectively as mathematical programming, and the potential application of such models to business problems and decision-making. Each section introduces and explains a specific type of mathematical programming model: the transportation and assignment models, the linear programming model and a number of more advanced models. Within each section, a typical business problem is investigated. A conceptual understanding of the solution method is then developed, followed by the mathematical underpinning to the technique under discussion. The wider management implications of the model are assessed in practical terms. Each chapter includes a series of student activities and exercises. Whenever possible the mathematical theory is kept to a minimum and the mathematics introduced is directly related to conceptual context of the problem.