Computer aided decision support system for water strategic planning in Jordan

The Nominal Group Technique and a multi-criteria decision aid software are utilised to develop a decision support system for strategic planning of water resources in Jordan. The system described is novel in that it integrates the various decision analytical management techniques in order to increase the flexibility and efficiency of the decision making process.     

Decision maker preferences for information in complex decision making: New directions for OR intervention

Operations research models are used in many business and non-business entities to support a variety of decision making activities, primarily well-defined, operational decisions. This is due to the traditional emphasis of these models on optimal solutions to pre-specified problems. Some attempts have been made to use OR models in support of more complex, strategic decision making. Traditionally, these models have been developed without explicit consideration for the information processing abilities and limitations of the decision makers, who interact with, provide input to, and receive output from such models.Research in judgement and decision making show that human decisions are influenced by a number of factors including, but not limited to, information presentation modes; information content, modes, e.g., quantitative versus qualitative; order effects such as primacy, recency; and simultaneous versus sequential presentation of data.This article presents empirical research findings involving executive business decision makers and their preferences for information in decision making scenarios. These preference functions were evaluated using OR techniques. The results indicate that decision makers view information in different ways. Some decision makers prefer qualitative, narrative, social information, whereas other prefer quantitative, numerical, firm specific information. Results also show that decision making tasks influence the preference structure of decision makers, but that in general, the preference are relatively stable across tasks.The results imply that for OR models to be more useful in support of non-routine decision making, attention needs to be focused on the information content and presentation effects of model inputs and outputs.     

Extending the multi-criteria decision making method DEX with numeric attributes,value distributions and relational models

Central European Journal of Operations Research - DEX is a qualitative multi-criteria decision analysis method. The method supports decision makers in making complex decisions based on multiple,...     

Dynamic multi-criteria evaluation of co-evolution strategies for solving stock trading problems

Risk and return are interdependent in a stock portfolio. To achieve the anticipated return, comparative risk should be considered simultaneously. However, complex investment environments and dynamic change in decision making criteria complicate forecasts of risk and return for various investment objects. Additionally, investors often fail to maximize their profits because of improper capital allocation. Although stock investment involves multi-criteria decision making (MCDM), traditional MCDM theory has two shortfalls: first, it is inappropriate for decisions that evolve with a changing environment; second, weight assignments for various criteria are often oversimplified and inconsistent with actual human thinking processes.In 1965, Rechenberg proposed evolution strategies for solving optimization problems involving real number parameters and addressed several flaws in traditional algorithms, such as their use of point search only and their high probability of falling into optimal solution area. In 1992, Hillis introduced the co-evolutionary concept that the evolution of living creatures is interactive with their environments (multi-criteria) and constantly improves the survivability of their genes, which then expedites evolutionary computation. Therefore, this research aimed to solve multi-criteria decision making problems of stock trading investment by integrating evolutionary strategies into the co-evolutionary criteria evaluation model. Since co-evolution strategies are self-calibrating, criteria evaluation can be based on changes in time and environment. Such changes not only correspond with human decision making patterns (i.e., evaluation of dynamic changes in criteria), but also address the weaknesses of multi-criteria decision making (i.e., simplified assignment of weights for various criteria).Co-evolutionary evolution strategies can identify the optimal capital portfolio and can help investors maximize their returns by optimizing the preoperational allocation of limited capital. This experimental study compared general evolution strategies with artificial neural forecast model, and found that co-evolutionary evolution strategies outperform general evolution strategies and substantially outperform artificial neural forecast models. The co-evolutionary criteria evaluation model avoids the problem of oversimplified adaptive functions adopted by general algorithms and the problem of favoring weights but failing to adaptively adjust to environmental change, which is a major limitation of traditional multi-criteria decision making. Doing so allows adaptation of various criteria in response to changes in various capital allocation chromosomes. Capital allocation chromosomes in the proposed model also adapt to various criteria and evolve in ways that resemble thinking patterns.     

基于改进的证据推理方法的多指标决策模型

对于一个多指标决策问题，证据理论可以通过构造辨识框架和基本概率分配函数、采取递归的证据合成方法。计算出原始数据在反映多个指标联合作用的情况下对不同判别结果的支持程度，并可以在信息复杂或数据不完整的条件下做出评估决策。本文首先建立基于证据推理的多指标评估问题的基本模型，然后引入了模糊数据方法以处理具有模糊概念或推理关系的复杂问题，同时还考虑了实际问题中可能出现加权证据或者相关证据的情况，其目的是为了建立一套具有实用性的、准确有效的多指标评估模型。文章最后设计一个风险评估的算例，分析了该方法的优点以及需要进一步完善之处。     

A network-based futures method for strategic business planning

Many strategic decisions in business are made in a context which the decision makers perceive as uncertain, complex and opaque. A method, based on Rhyne's field anomaly relaxation technique, is described of generating a network of states which characterise the environment or context in which strategic decisions are to be made. These states represent possible future conditions for the business, and knowledge of them allows improved strategic understanding and decision making to be achieved. This paper describes the method, using a representative real-life application to illustrate the process.     

Are multi-criteria decision-making tools useful? An experimental comparative study of three methods

Many decision makers still question the usefulness of multi-criteria decision-making methods and prefer to rely on intuitive decisions. In this study we evaluated a number of multi-criteria decision-making tools for their usefulness using incentive-based experiments, which is a novel approach in operations research but common in psychology and experimental economics. In this experiment the participants were asked to compare five coffee shops to win a voucher for their best-rated shop. We found that, although the usefulness of different multi-criteria decision-making tools varied to some extent, all the tools were found to be useful in the sense that, when they decided to change their ranking, they followed the recommendation of the multi-criteria decision-making tool. Moreover, the level of inconsistency in the judgements provided had no significant effect on the usefulness of these tools.     

A multi-criteria optimization model for humanitarian aid distribution

Natural disasters are phenomenons which strike countries all around the world. Sometimes, either by the intensity of the phenomenon or the vulnerability of the country, help is requested from the rest of the world and relief organizations respond by delivering basic aid to those in need. Humanitarian logistics is a critical factor in managing relief operations and, in general, there is a lack of attention on the development of mathematical models and solution algorithms for strategic and tactical decisions in this area. We acknowledge that in humanitarian logistics traditional cost minimizing measures are not central, and postulate that other performance measures such as time of response, equity of the distribution or reliability and security of the operation routes become more relevant. In this paper several criteria for an aid distribution problem are proposed and a multi-criteria optimization model dealing with all these aspects is developed. This model is the core of a decision support system under development to assist organizations in charge of the distribution of humanitarian aid. Once the proposed criteria and the model are described, an illustrative case study based on the 2010 Haiti catastrophic earthquake is presented, showing the usefulness of the proposal.     

Transparent prioritisation,budgeting and resource allocation with multi-criteria decision analysis and decision conferencing

Managers in both for-profit and not-for-profit organisations continually face the task of allocating resources by balancing costs, benefits and risks and gaining commitment by a wide constituency of stakeholders to those decisions. This task is complex and difficult because many options are present, benefits and risks are rarely expressed as single objectives, multiple stakeholders with different agendas compete for limited resources, individually optimal resource allocations to organisational units are rarely collectively optimal, and those dissatisfied with the decisions taken may resist implementation. We first explain three current approaches to resource allocation taken from corporate finance, operational research and decision analysis, and we identify a common mistake organisations make in allocating resources. The paper then presents a technical process, multi-criteria portfolio analysis, for balancing the conflicting elements of the problem, and a social process, decision conferencing, which engages all the key players during the modelling process, ensuring their ownership of the model and the subsequent implementation. This socio-technical process improves communication within the organisation, develops shared understanding of the portfolio and generates a sense of common purpose about those projects that will best realise the organisation’s objectives. The paper concludes with lessons we have learned from actual practice. The authors want to thank Allergan and FCT (Portuguese Science Foundation) for their support.     

A confidence voting process for ranking problems based on support vector machines

In this paper, we deal with ranking problems arising from various data mining applications where the major task is to train a rank-prediction model to assign every instance a rank. We first discuss the merits and potential disadvantages of two existing popular approaches for ranking problems: the ‘Max-Wins’ voting process based on multi-class support vector machines (SVMs) and the model based on multi-criteria decision making. We then propose a confidence voting process for ranking problems based on SVMs, which can be viewed as a combination of the SVM approach and the multi-criteria decision making model. Promising numerical experiments based on the new model are reported. The research of the last author was supported by the grant #R.PG 0048923 of NESERC, the MITACS project “New Interior Point Methods and Software for Convex Conic-Linear Optimization and Their Application to Solve VLSI Circuit Layout Problems” and the Canada Researcher Chair Program.     

Numerical scaling of ratio scale utilities in multi-criteria decision analysis with geometric model

The ratio scale measurement of utilities in multi-criteria decision analysis has been criticised due to theoretical and practical interpretation of the required assessments. Compared to the ratio scale models, for example, the ‘0–1-scale’ models based on interval scale have been more generally accepted. On the other hand, under some conditions it has been shown that the results of multi-criteria decision support based on ratio scale comparisons are actually independent of the numerical magnitude of the ratio scale assessments. This paper reviews and interprets these results and proposes new solutions for the remaining problems, for which the numerical magnitude of the ratio scale utilities is required. Moreover, we interpret the scale-independent ratio scale models with respect to some other multi-criteria decision support models. The theoretical analysis is carried out by statistical models and illustrated by numerical examples.     

三角模糊数去模糊化对VIKOR妥协解的影响研究

针对准则值和准则权重均为三角模糊数的多准则决策问题,研究了不同三角模糊数去模糊化方法适用的数学运算规则,应用VIKOR方法进行三角模糊数去模糊化的必要环节和前提条件,分析了去模糊化对群体效用值和个体遗憾值以及对妥协解的影响机制,给出了一种拓展的VIKOR方法的决策步骤,最后运用算例说明了方法的实施过程和有效性。     

Multi-criteria analysis for dredger dispatching under uncertainty

Dredger dispatching is a complex decision making process in which multiple requirements and uncertain site conditions have to be taken into consideration simultaneously, for a specific dredging task. In evaluating the suitability of dredgers, besides quantitative assessments, qualitative assessments are often required to deal with uncertainty, subjectiveness and imprecision, which are best represented with fuzzy data. This paper formulates dredger dispatching as a fuzzy multi-criteria analysis model, and presents an effective algorithm for handling both crisp and fuzzy data in a straightforward manner. As a result, effective decisions can be made based on consistent evaluation results. An empirical study of a real case in China is conducted to demonstrate the applicability of the model. With its simplicity in both concept and computation, the model can be implemented as an effective decision aid in selecting dredgers for specific dredging tasks.     

Executive views concerning decision support tools

Support tools for strategic-level decision-making have become increasingly popular. This study investigates the role of OR/MS tools in today’s strategic-level decision support tool market. Executives working in Finland’s 500 largest companies were asked about the decision support tools they use when making major decisions. The responses received indicated that executives actively use a variety of tools, and an average of five different strategic-level tools. Approximately 10% of the tools used could be identified as OR/MS type, these often suit the needs of larger companies with strategic logistical or production functions and compared to other tools, have a specific profile. Executives see advantages in using tools that provide cognitive, collaboration and communication possibilities, and also in using tools that make processes more efficient. OR methodologies have influenced some of the other tools on the market, but ‘soft OR’ tool usage could not be identified. Tools which support creativity are needed.     

一种基于证据推理的信息不完全的多准则决策方法

针对权系数信息不完全、准则值不确定且不完全的多准则决策问题,提出了一种基于证据推理的方法.该方法通过证据推理算法构造方案的目标函数,结合不完全信息的权系数建立非线性规划模型,使用遗传算法求解模型得到效用值的区间数,从而得到整个方案集的排序.最后以实例表明该方法的有效性和可行性.     

基于前景云的不确定语言多准则国际股指投资群决策

针对投资决策过程中语言评价值具有随机性及模糊性,以及投资者的决策容易受到其情绪的影响且不同投资者受到的影响程度不同,本文提出基于前景云的不确定语言多准则投资群决策方法,并将其运用在国际股指投资中。其中,前景理论模型用来刻画投资者情绪对决策的影响,而云模型用来刻画语言评价值模糊性和随机性之间的关联。更具体来说,论文首先解决传统文献云生成方法中云期望值超过论域或者无法区分语言评价标度等级等问题,然后构建了前景云模型并将该模型应用于多个专家共同进行的国际股指投资群决策。实证结果显示,该模型得出的决策结果比传统决策方法下的结果更直观、可靠,表现为决策依据不仅考虑方案的期望值大小及变动风险,而且还考虑了投资者情绪对决策的影响。由此可得出,本文所提出的模型更符合现实情景,也更能有效实现对投资群决策。     

Linking stakeholder visions with resource allocation scenarios and multi-criteria assessment

Stakeholders and decision makers often develop visions of the ideal-type future as a response to complex societal problems and design their actions accordingly. However, these actors sometimes have a limited understanding as to whether their visions are feasible, what action is required and what the potential consequences are. This paper presents a methodology for linking visions with quantitative resource allocation scenarios which show different options in implementing the visions. The consequences are then appraised by multi-criteria assessment in order to find optimal and acceptable ways of implementation. As a result, stakeholders and decision makers learn about their visions and may even rethink them before decision making. The methodology thus couples visionary ideas with analytical information, providing a novel approach using quantitative techniques in a soft framework. The methodology is illustrated via a real-world case study concerning the future energy system in a small Swiss community.     

A general model for voting systems with multiple alternatives

In this paper, the extension of simple games to the vector case is proposed. Games with multiple qualitative criteria and multi-criteria simple games are introduced as a natural tool for modelling voting systems and related social-choice situations. After formally defining these games, the special class of monotonic multi-criteria simple games is characterized. We show that these games enable the formulation and analysis of several collective decision models proposed in the literature. Furthermore, our model can be applied to group-decision problems which cannot be analyzed in the existing frameworks.     

A new multi-criteria approach dealing with dependent and heterogeneous criteria for end-of-life product strategy

Strict regulations, technological growth and environmental impacts are influent factors in the choice of the best strategy for end-of-life (EOL) product. In fact, EOL is one stage of the life cycle having gained the attention of the market.This study proposes an integrated methodology that relies on multi-criteria analysis and takes into account both quantitative and qualitative criteria while respecting mutual interactions between them. This has been performed by introducing, on the one hand, the 2-tuple linguistic representation model dealing with non-homogeneous information data, and on the other hand, the Choquet integral interaction modeling between criteria into the PROMETHEE method. Although it has been developed for EOL selection problems, the proposed method fits to all kinds of decision-making problems with heterogeneous information. As this work demonstrates, this multi-criteria analysis approach can offer a technical-scientific decision making support tool in the EOL product sector. We also perform a sensitivity to reveal the effect of the subjective parameter variations on the originally resulted ranking.