一种策略层项目计划的双目标优化方法

针对产品开发项目管理的实际情况,对策略层计划优化方法进行研究。以工作包的工作量估算为基础,以资源投入水平和工期最小化为目标,考虑各种约束条件,提出一种策略层项目计划问题的混合整数规划问题模型。以非支配遗传算法NSGA-II为基础框架,设计了一种改进的双目标遗传算法。该算法针对问题的特点,提出了基于资源平滑的解码算法。参考NSGA-III的关键特征,对拥挤密度计算方法进行改进。通过企业实际项目案例,验证了算法的性能和所提出的策略层项目计划方法的有效性。     

Review of Empirical Studies in Multiobjective Mathematical Programming: Subject Reflection of Nonlinear Utility and Learning

Multiple objective programming provides a means of aiding decision makers facing complex decisions where trade-offs among conflicting objectives must be reconciled. Interactive multiobjective programming provides a means for decision makers to learn what these trade-offs involve, while the mathematical program generates solutions that seek improvement of the implied utility of the decision maker. A variety of multiobjective programming techniques have been presented in the multicriteria decision-making literature. This study reviews published studies with human subjects where some of these techniques were applied. While all of the techniques have the ability to support decision makers under conditions of multiple objectives, a number of features in applying these systems have been tested by these studies. A general evolution of techniques is traced, starting with methods relying upon linear combinations of value, to more recent methods capable of reflecting nonlinear trade-offs of value. Support of nonlinear utility and enhancing decision-maker learning are considered.     

PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEM DESIGN

Top-level decision making in business organizations is characterized by high degrees of uncertainty, incomplete information, and conflicting objectives. To support top-level decision making effectively, decision support systems (DSSs) have been proposed. Information supplied by a DSS must be selective in that not all possible information sets may be feasibly or economically represented in the data base. This study suggests that discovery of perceptual complexity (dimensionality) of information items, and the subsequent categorization of decision makers having the same perceptions of those information items, is a first step in the ultimate design of an effective DSS. Through the use of multidimensional scaling in a field setting, this study shows the feasibility of creating relatively homogeneous groups of decision makers according to the content and number of dimensions associated with various information items. Further results of the research suggest that information can be tailored to classes of users, which has cost-benefit implications as well as the potential to improve the quality of the resultant decisions.     

Interactive Multiple Objective Decision Support for Sales Force Sizing and Deployment*

An interactive decision aid is introduced for the deployment of two sales resources: salespeople and sales support staff. The aid consists of a normative sales resource allocation model with five objectives and an interactive multiple objective programming solution procedure. The specific decision problem addressed involves the assignment of salespeople and sales support people to customer accounts and the allocation of the time they spend on these accounts. The authors contribute to the existing sales resource modeling literature by dealing with the deployment of two sales resources and interactively solving this problem with respect to five short-run and long-run objectives of the firm. This approach differs from existing sales force modeling efforts in which the solution is found noninteractively by optimizing a single sales resource model with respect to a single objective, often short-run sales. An application of the decision aid to the deployment problem of an industrial sales force manager is presented. Furthermore, useful extensions of the basic sales resource allocation model are discussed.     

Data and Model Management in a Generalized MCDM-DSS*

Drawing upon the choice models developed in the multiple criteria decision making (MCDM) area, this paper proposes an architecture for designing an intelligent decision support system (DSS) that is intended to aid in making choices among multiple alternatives along multiple dimensions. It argues that effective support can be provided to the decision maker when the knowledge-based DSS is capable of dynamically selecting choice models appropriate to the domain and context of a particular problem being specified by the decision maker, and of properly applying them to the problem solution. Development of a prototype intended to partially represent application of the architecture is described. The paper concludes with suggestions for research extensions.     

An Empirical Investigation of the Effects of Decision Aids on Problem-Solving Processes*

Despite the growing number of investigations examining decision support systems (DSS), relatively few empirical studies have evaluated the effects of DSS on problem-solving processes. This study uses protocol analysis to investigate the impact of a specific decision aid on problem-solving processes in a semi-structured problem. Results indicate that decision aids influence the problem-solving processes of decision makers. The effect of a decision aid is found to be contingent on familiarity with the decision aid, task familiarity, and the interaction of these two factors. Suggestions for incorporating interaction effects and problem-solving processes into future examinations are proposed.     

An Interactive Framework for Multi-Person,Multiobjective Decisions

Group decision making in the presence of multiple conflicting objectives is complex and difficult. This paper describes and evaluates an iterative technique to facilitate multiple objective decision making by multiple decision makers. The proposed method augments an interactive multiobjective optimization procedure with a preference ranking tool and a consensus ranking heuristic. Two multiple objective linear programming (MOLP) solution approaches, the SIMOLP method of Reeves and Franz [39] and the interactive weighted Tchebycheff procedure of Steuer and Choo [49], are recommended optimization strategies to be used independently or in concert. Computational experience suggests that the proposed framework is an effective decision-making tool. The procedure quickly located excellent compromise solutions in a series of test problems with hypothetical decision makers. In addition, human decision makers gave positive evaluations of the procedure and the production plans the procedure provided for a resource allocation case problem.     

EDUCATION

The power of an integer programming approach—and more particularly a 0,1 programming approach—to resource allocation problems is not widely appreciated. Recent developments in mathematical programming and in problem formulation enable decision makers to deal explicitly with the special conditions which characterize real world problems in capital budgeting, scheduling, and facilities planning. In this paper, somewhat tutorial in nature, we seek to demonstrate formulation and solution of an equipment selection resource allocation problem with several special conditions. The problem can be solved on any reasonably equipped computer system. Sensitivity studies are also performed and discussed.     

Selecting a Portfolio of Technologies: An Application of Decision Analysis

The Department of Energy is faced with the critical and complex decision of selecting technologies for waste site remediation. This research focuses on developing a decision support tool which assists the decision maker to find an optimal portfolio. A portfolio consists of selecting the appropriate processes for a remediation site and, subsequently, selecting a technology for each process so that the decision maker's objectives are achieved. The measures supporting the objectives are risk, life-cycle cost, and time required for remediation. The model uses exponential attribute utility functions with an additive objective function. The model provides the decision maker with estimates of the cost and time distributions, and their associated utility. Cumulative frequency distributions illustrate the dominance of technology choices and the variance in the results. The model permits sensitivity analysis in the form of rainbow and tornado diagrams to display the effects of changes in the values of the input variables. Overall, the model provides a generic technology selection tool that can be used to make better informed decisions and may be easily manipulated to reflect changes in the remediation process.     

COGNITIVE STYLE AND THE USEFULNESS OF INFORMATION*

The desirability of a merger/acquisition alternative depends in part on the perceptions of the decision maker. What sources of information are “useful” to the decision maker & Does the set of useful information remain constant for all decision makers; if not, do individuals using similar information sets have similar information processing characteristics? Do these sets vary as feedback is obtained during the decision process? To answer these questions, graduate students participated in a modified Delphi experiment, and the resulting data were analyzed by the two-way aligned-ranks nonparametric test. These test results affirm that in a merger/acquisition scenario, decision makers with different cognitive styles prefer different sets of information and these sets vary dynamically as feedback is incorporated in the decision-making process. Furthermore, information that contains worker and community welfare considerations is identified as “useful” five times more frequently by decision makers with a “feeling” cognitive style than those with a “thinking” style.     

Strategic group decision support systems--a guide for the unwary

Considerable interest is currently being shown in the use of information technology to assist in improving group process, particularly those associated with strategic planning. Three major approaches are developing to provide this support, and these are described in this article. In general, articles about Group DSS are overwhelmingly favourable to the approaches, although research findings suggest that some forms of Group DSS can have deleterious effects on the quality of meetings. These research findings are discussed.     

The Influences of User Characteristics on Performance in a Logistics DSS Application

Decision Support Systems (DSS) are widely used in logistics decision applications, and a large number and variety of systems are commercially available. We investigate the contributions of user characteristics including experiences, data preferences, intuition, and effort to decision performance in a logistics DSS context. The study includes a laboratory experiment in which decision makers with varied experiences used a DSS to make facility network design decisions for problems of varying complexity. Two variants of the DSS are utilized in order to examine the interactions of a DSS decision aid with user characteristics. We find that intuition and effort are associated with decision-making performance. High analytic ability is not related to intuition, however. Education and previous experience are associated with performance. Yet these characteristics are also unrelated to intuition. Decision makers who highly value disaggregated data provided by the DSS tend to perform poorly. Also, the results suggest that the effects of users' experiences and preferences on performance are influenced by an analytical decision aid.     

Complexity Factors and Intuition-based Methods for Facility Network Design

Logistics managers frequently utilize decision support systems (DSS) to make facility network design decisions. Many DSS do not provide optimization capabilities, but instead rely on scenario evaluation as a means for developing solutions. We experimentally assessed the performances of decision makers, including experienced managers, who used four variants of a scenario evaluation-based DSS to solve realistically sized network design problems of varying complexities. Complexity factors included DSS attributes, problem size, network types, and demand dispersion patterns. Decision makers' performances were assessed relative to optimal solutions. Overall, the decision makers generated relatively high-quality solutions using the DSS variants. The type of design problem solved did not significantly impact problem-solving performance. However, performance degraded and variability in solution quality escalated as problem size was increased. The availability of incremental solution cost improvement cues in the DSS significantly improved solution quality and reduced performance variability. Iconic graphic enhancements to the DSS did not consistently affect performance. However, significant interactions existed among the effects of DSS graphics capabilities, DSS information cues, and problem attributes.     

A Decision Support System for Production/ Distribution Planning in Continuous Manufacturing

This paper presents a decision support system (DSS) for managing production/distribution planning in a continuous manufacturing environment. The vendor has multiple plants and distribution centers (DCs). The trading partners have widely varying independent demand patterns. The DSS is designed for use in a multiproduct environment with overlapping raw materials and processing requirements. The production and distribution lead times at plants may span multiple planning periods. The impact of any manual override of a suggested solution can also be evaluated. The DSS is based on a linear programming model with a rolling horizon and was originally designed for a large process industry. Results of a pilot implementation using actual data are also presented, which show potential for significant savings for the company.     

PREFERENCE MAPPING OF PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEMS DESIGN

In a recent issue of this journal, Watkins [13] presented an approach for discovery of decision-maker perceptions of the complexity (dimensionality) of information items that might be supplied by a decision support system. Through use of multidimensional scaling and cluster analysis, relatively homogeneous groups of decision makers, sharing common perceptions of various information items, were formed. This prior research was referred to as a first step in suggesting that information reports could be tailored to groups of decision makers classified on the basis of common perceptions of information. The current research extends the prior study by evaluating decision maker preferences for information in a variety of decision-making scenarios in relation to the previously identified perceptions of the information. Based on the results of the study, conclusions are made which suggest that the tailoring of information to groups of decision makers should be based on both perceptions and preferences for information. Even so, it is demonstrated that the decision tasks have an impact on the preferences for information which may affect the attempt to tailor information to groups of decision makers.     

BPR决策支持系统分布式求解模型的研究

基于多Ａｇｅｎｔ规划技术,提出并建立了支持企业过程重组（ＢＰＲ）的决策支持系统的分布式协同求解模型,包括企业过程的分层规划理论、多Ａｇｅｎｔ协同模式分析、状态空间模型以及任务分解算法等四部分内容．它的提出为企业过程重组的工具支持提供了理论依据和技术方法．实践证明,应用该技术可以有效地指导ＢＰＲＤＳＳ的开发     

A survey of goal programming

In this paper the applications of goal programming to industrial and economic planning are reviewed, and it is shown how the linear programming framework can be extended to include a series of goals (or objectives). A planning method is suggested in which the decision maker is presented with a list of all the possible attainable goals from which he picks the most appropriate set.     

Power planning in ICT infrastructure: A multi-criteria operational performance evaluation approach

It is critical for information and communications technology (ICT) companies to carry our effective power planning, in order to support the growing number of services they provide, and this traditionally relies on the tacit knowledge and experience of senior staff. The loss of such domain knowledge resulting from the retirement of staff is an important issue for organizations such as Chunghwa Telecom (CHT), the largest ICT operator in Taiwan. This study thus develops a systematic power planning model using a multi-criteria operational performance evaluation. A group version of the fuzzy repertory grid and fuzzy TOPSIS approaches is applied to elicit a set of evaluation criteria that senior staff agree on, and then the priorities of the telecom rooms are evaluated against this. In addition, a new factor, reflecting the attitudes of the decision makers with respect to the degree of strictness, is defined to determine the superiority and inferiority of each alternative compared to the others. Furthermore, a novel decision aggregation strategy regarding the degree of variation among decision makers is proposed, and a quantitative assessment is carried out to analyze its impact on the ranking results in an objective manner. The proposed model may help ICT organizations to more effectively manage their power resources, and thus obtain competitive advantages.     

Corporate prediction markets: a tool for predicting market shares

Prediction markets have been applied for various forecasting issues, such as political events or sports. The ability of these markets to collect distributed information in a fast and efficient way provides useful support for corporate planning. A crucial criterion for the quality of the information aggregation process is the liquidity of the market, especially in corporate prediction markets, which typically consist of fewer traders than public markets. The use of automated market makers is one option with which to ensure enough liquidity, but it is always related to some drawbacks. This paper investigates a field study of a corporate prediction market that replaces the automated market maker with human traders. We analyze the efficiency of such markets, the impact of the applied incentive system and the effects of human market makers.     

An Experimental Evaluation of Articulation of Preferences in Multiple Criterion Decision-Making (MCDM) Methods

This paper describes the results of a study done to determine how well multiple criterion decision-making methods perform in helping a decision maker arrive at a preferred solution to a multicriterion problem with conflicting objectives. The study used a factorial experiment and doctoral students as subjects. Two competing methods for solving multicriterion problems were compared along with the influence of problem complexity. The methods differed in the way preferences were articulated by decision makers. The results showed that there was no difference between the methods for several performance measures, disaffirming some prior expectations. From an actual use point of view, the study suggests that methodological improvements to existing techniques must be matched by efforts to improve information presentation and interpretation to facilitate preference judgments.