Supporting Learning in Evolving Dynamic Environments

In dynamic decision environments such as direct sales, customer support, and electronically mediated bargaining, decision makers execute sequences of interdependent decisions under time pressure. Past decision support systems have focused on substituting for decision makers' cognitive deficits by relieving them of the need to explicitly account for sequential dependencies. However, these systems themselves are fragile to change and, further, do not enhance decision makers' own adaptive capacities. This study presents an alternative strategy that defines information systems requirements in terms of enhancing decision makers' adaptation. In so doing, the study introduces a simulation model of how decision makers learn patterns of sequential dependency. When a system was used to manage workflows in a way predicted by the model to enhance learning, decision makers in a bargaining experiment learned underlying patterns of sequential dependencythat helped them adapt to new situations. This result is rare if not unique in the study of dynamic decision environments. It indicates that a shift, away from substituting for short-term deficits and toward enhancing pattern learning, can substantially improve the effectiveness of decision support in dynamic environments. Based on the specific findings in this study, this shift has important implications for designing information system workflows and potential future applications in interface design.     

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.     

Innovative research in OR/MS?

This paper is a contribution to the continuing debate about research priorities and publications in OR/MS. It categorises research publications in several different ways. First it uses approaches suggested in the information systems and operations management literature. It then takes previous examinations of leading OR/MS journals to gain a different perspective on the same issues. Finally, it uses a multi-faceted view of OR/MS to try to capture its full richness. These analyses confirm the view that much published research in OR is unengaged and focuses on decision mathematics or optimisation, apparently for its own sake. That is, most papers published in the leading OR/MS journals take little or no account of how their findings might be used in practice, nor do they express much concern about this issue. The reasons for this state of affairs are discussed, so as to consider whether a change might be overdue.     

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.     

Why modelling and model use matter

When OR/MS analysts develop a model, how are they intending this model to be used? There are many different ways in which OR/MS models may be classified and one important categorisation is the intended use of the model. Some models are intended for routine use on a frequent basis, with little or no human intervention. Others form part of human decision process and provide support to that process. Considering model validation, data requirements, added value and possible pitfalls leads to a theory of model use based on four categories: decision automation, routine decision support, investigation and improvement, and generating insights for debate. A pilot investigation in an OR/MS group demonstrates that this categorisation could provide the basis for empirical research into a theory of model use in operational research. A theory of model use would be of value to academics, who could prioritise their work, and to practitioners, who could place their own work in a broader landscape.     

A survey of decision support system applications (1988–1994)

To extend a previous survey of specific decision support system (DSS) applications over the period (January 1971–April 1988), we have conducted a follow-up survey of DSS applications published between May 1988 and December 1994. Two hundred seventy-one published applications are identified. This survey reveals that there appear to be more creative applications of optimisation and suggestion model-based DSS than simulation-based applications. This is evidenced by a proportional increase of optimisation and suggestion models and a decrease of representation models. Moreover, group decision support systems, executive support systems, and knowledge-based systems applications are becoming more prevalent in many organisations. Although management science (MS)/operational research (OR) models continue to play critical roles, there is a clear observable trend in the DSS model area that three non-MS/OR tools are emerging as powerful DSS tools: graphics, artificial intelligence, and visual interactive modeling.     

Design of an IT-driven decision support system for vehicle routing and scheduling

This paper presents the development of a decision support system used by an oil downstream company for routing and scheduling purposes. The studied problem refers to a complex delivery process of oil products from a number of distribution centers to all customers. The latest rapid advance of operations research (OR) applications, in the form of advanced planning and scheduling (APS) systems, has shown that OR algorithms can be applied in practice if (a) they are embodied in packaged information technology (IT) solutions, (b) the interface problems to mainstream ERP software applications are solved. In this study the utilisation of advanced IT systems supports effectively the planning and management of distribution operations. The combination of a supply chain management (SCM) application with a geographical information system (GIS) integrated with an enterprise resource planning (ERP) software resulted to this innovative decision support tool. The objectives of this new tool are: optimum use of the distribution network resources, transportation cost reduction and customer service improvement. The paper concludes with the benefits of the new system, emphasising at how new technologies can support transportation processes with the help of operations research algorithms embedded in software applications.     

The development of management sciences/operational research discourses: surveying the trends in the US and the UK

This paper explores the trends in American and British management science/operational research (MS/OR) during the last 25 years. We argue that British MS/OR has developed a soft and systemic approach to MS/OR practice, which has resulted in the emergence of a number of interpretive and critical-oriented methodologies. American MS/OR practice has remained closed to the positivistic discourse. Using a set of keywords and authors’ names associated with the main features of the interpretive and critical MS discourses, we surveyed articles published in three major US MS/OR journals. We compare these results with trends in the UK MS/OR scene. Findings appear to confirm the different directions taken by the MS/OR practice across the Atlantic. The paper posits possible reasons underpinning these differences: firstly, the particular methodological path followed by the British MS/OR, from early ‘soft systems’ applications in the early 1970s to the now well-established ‘Problem Structuring Methods’; and secondly, continuous engagement between the systems and MS/OR British communities (a dialogue that seems not to have occurred in the US). The paper contributes to a reflection on the MS/OR historical developments and contrasts these developments in both countries, two areas of OR significantly under-researched.     

Preference elicitation for a ranking method based on multiple reference profiles

4OR - Multiple criteria decision aid methodologies support decision makers (DM) facing decisions involving conflicting objectives. DM’s preferences should be captured to provide meaningful...     

Management science methodologies in environmental management and sustainability: discourses and applications

This paper investigates and discusses the use of systemic methodologies (SMs) developed in management science/operational research (MS/OR), in particular, those SM that have been informing the complexity inherent in environmental management and sustainable (EM/S) practices. By surveying a sample of the top MS/OR and systems journals, we assess the extent to which systemic management science methodologies developed recently have been used in tackling EM/S problems. Titles and abstracts of EM/S applications published in MS/OR and systems journals between 1989 and 2009 were queried for the occurrence of typical keywords associated with a set of SMs (eg, complexity theory, systems dynamics, soft systems, critical systems, viable systems model). The survey identifies a set of articles representing the practice of either a particular methodology or of a mixture of various SMs in EM/S setting. By assembling and critically reviewing a sample of applications in EM/S the paper hopes to raise awareness among environmentalists, operational researchers and management scientists of the benefits of using systemic approaches developed in MS/OR and, in this way, to encourage further exchange and conversation between these fields of management.     

Why Stratification of Networks Emerges in Innovative Society: Intelligent Poly-Agent Systems Approach

This paper rigorously shows in the framework of poly-agent systems theory that it is very natural for an innovative society to emerge stratification of networks to cope with complexity intelligent decision makers of it have to deal with. Before introducing poly-agent systems theory, I will first refer to empirical observations of emergence of stratification of networks in innovative societies, which motivate this research. I, then, theoretically show that coexistence of both networks and hierarchies is reasonable and inevitable for a tightly interrelated society because it can provide the decision makers with mediation, which is beneficial for the decision makers as well as the society as a whole. Finally, I will go back again to implications from our theoretical study.     

基于新直觉模糊相似度的大规模群决策方法

研究了群体规模较大情况下基于直觉模糊评价信息的决策方法。提出一种新的直觉模糊相似度公式,研究了一种新的直觉模糊聚类方法,设计了一种基于新的聚类方法的核心决策者权重确定方法。实例分析说明了该方法的合理性和可行性。     

Connecting a population dynamic model with a multi-period location-allocation problem for post-disaster relief operations

In this study, we propose a mathematical model and heuristics for solving a multi-period location-allocation problem in post-disaster operations, which takes into account the impact of distribution over the population. Logistics restrictions such as human and financial resources are considered. In addition, a brief review on resilience system models is provided, as well as their connection with quantitative models for post-disaster relief operations. In particular, we highlight how one can improve resilience by means of OR/MS strategies. Then, a simpler resilience schema is proposed, which better reflects an active system for providing humanitarian aid in post-disaster operations, similar to the model focused in this work. The proposed model is non-linear and solved by a decomposition approach: the master level problem is addressed by a non-linear solver, while the slave subproblem is treated as a black-box coupling heuristics and a Variable Neighborhood Descent local search. Computational experiments have been done using several scenarios, and real data from Belo Horizonte city in Brazil.     

The practice of operational research in Taiwan

This paper presents the results of a questionnaire survey of operational research/management science (OR/MS) practices in Taiwanese companies. The survey was addressed to the current status and future perspectives of OR/MS in Taiwan. During the spring of 2001, 2000 questionnaires were mailed to the top 1000 domestic manufacturing firms and top 1000 domestic service organizations. These asked questions concerning specific OR/MS techniques being used, application areas of OR/MS, reasons for using OR/MS, reasons for not using OR/MS, difficulties encountered practically, and future perspectives. Results from 262 valid respondents provided several informative findings. Compared with the 1995 survey of Kao et al, it found that the percentage of companies that have used OR/MS techniques increased from 62.7% in 1995 to 76.7% in 2001. Also, the percentage of companies that have never heard of OR/MS decreased from 16.1% in 1995 to 11.1% in 2001. Because of the Taiwan government recently developing educational and training programs in OR/MS, it found that the importance of OR/MS has been recognized by Taiwan companies as an efficient management tool for economic development, and the usage of OR/MS will continuously increase.     

A Levinson-like algorithm for symmetric strongly nonsingular higher order semiseparable plus band matrices

In this paper, we will derive a solver for a symmetric strongly nonsingular higher order generator representable semiseparable plus band matrix. The solver we will derive is based on the Levinson algorithm, which is used for solving strongly nonsingular Toeplitz systems.     

Reducing the graphical user interface of a dynamic geometry system

Graphical user interfaces (GUIs) of dynamic or interactive geometry software (DGS) allow users to interact with the DGS by using a computer mouse. Clicking on a GUI icon performs an action like choosing a construction tool or manipulating an object. For novices, it may be difficult to recognize and recall the icons needed for a task. Learning mathematics and learning the use of a dynamic geometry system at the same time could lead to cognitive overload. Several DGS systems try to solve this problem by offering different GUIs: expert users can choose between a wide range of icons, while for novice users only the most basic icons are presented. By preselecting a specific set of icons, a teacher can adapt a DGS to create a tool, which meets specific pedagogical demands. Two experiments were conducted to investigate the effects of reducing GUIs of a DGS. In experiment 1, which was carried out with full and reduced interfaces of the DGS Cinderella, the eye movements and gaze points of the users were recorded by an eye tracker. The time taken by users to find given icons in different types of interfaces was measured. In experiment 2, students measured the angle sums of polygons using the DGS Cinderella with a full or a reduced interface. No significant effects of GUI reduction were found in both experiments. The results are discussed and ideas for future research are presented.     

Visualizing preferences on spheres for group decisions based on multiplicative preference relations

Decision makers’ choices are often influenced by visual background information. One of the difficulties in group decision is that decision makers may bias their judgment in order to increase the possibility of a preferred result. Hence, the method used to provide visual aids in helping decision making teams both to observe the background context and to perceive outliers is an important issue to consider. This study proposes an extended Decision Ball model to visualize a group’s decisions. By observing the Decision Balls, each decision maker can: see individual ranking as well as similarities between alternatives, identify the differences between individual judgments and the group’s collective opinion, observe the clusters of alternatives as well as clusters of decision makers, and discover outliers. Thus, this method can help decision makers make a more objective judgment.     

On computational methods for solutions of multiobjective linear production programming games

In this paper we consider a production model in which multiple decision makers pool resources to produce finished goods. Such a production model, which is assumed to be linear, can be formulated as a multiobjective linear programming problem. It is shown that a multi-commodity game arises from the multiobjective linear production programming problem with multiple decision makers and such a game is referred to as a multiobjective linear production programming game. The characteristic sets in the game can be obtained by finding the set of all the Pareto extreme points of the multiobjective programming problem. It is proven that the core of the game is not empty, and points in the core are computed by using the duality theory of multiobjective linear programming problems. Moreover, the least core and the nucleolus of the game are examined. Finally, we consider a situation that decision makers first optimize their multiobjective linear production programming problem and then they examine allocation of profits and/or costs. Computational methods are developed and illustrative numerical examples are given.     

An asynchronous direct solver for banded linear systems

Banded linear systems occur frequently in mathematics and physics. However, direct solvers for large systems cannot be performed in parallel without communication. The aim of this paper is to develop a general asymmetric banded solver with a direct approach that scales across many processors efficiently. The key mechanism behind this is that reduction to a row-echelon form is not required by the solver. The method requires more floating point calculations than a standard solver such as LU decomposition, but by leveraging multiple processors the overall solution time is reduced. We present a solver using a superposition approach that decomposes the original linear system into q subsystems, where q is the number of superdiagonals. These methods show optimal computational cost when q processors are available because each system can be solved in parallel asynchronously. This is followed by a q×q dense constraint matrix problem that is solved before a final vectorized superposition is performed. Reduction to row echelon form is not required by the solver, and hence the method avoids fill-in. The algorithm is first developed for tridiagonal systems followed by an extension to arbitrary banded systems. Accuracy and performance is compared with existing solvers and software is provided in the supplementary material.