An adaptive memory programming method for risk logistics operations

This paper presents a decision support system (DSS) that enables logistics planners of a well-known hank to design intra-city safe delivery routes, using an intelligent metaheuristic method and exploiting risk methodologies and spatial data information. The DSS routes minimize the probability of successful vehicle robbery at a certain point of the road network and satisfy all operational constraints of the distribution problem examined. The proposed DSS was implemented to an actual banking environment and the results obtained by this real-life application are reported.     

The FALCON decision support system: Preparing communities for weapons of opportunity

Since September 11, 2001, awareness of potential terrorist targets has increased greatly. Industrial chemicals, either in storage or transport, are now considered dangerously accessible materials that could be used to cause substantial harm. In response to this new threat, emergency organizations are beginning to plan for such possible chemical releases. Currently there is no tool that allows a community to track, analyze, query, and display data about these chemical “weapons of opportunity” and the readiness of the communities around them.Decision support systems are computer environments designed to assist decision makers within a particular problem-solving context. A particular type of DSS, environmental decision support systems (EDSS), assists environmental scientists and planners in making environmental management decisions. A hazardous materials decision support system called “FALCON” will assist emergency organizations by integrating information describing chemical inventories, security, health readiness, geography, and population into one information system. Emergency organizations will be able to assess response readiness of a community for chemical releases and prioritize antidote stockpiling, training, and security. Emergency organizations and first responders will use the FALCON DSS to simulate and prepare for real-time events, assess possible casualties, and receive emergency contact information. And with the help of FALCON, law enforcement and security personnel will be able to evaluate and augment protection of the most dangerous facilities.     

Spatial point process models for location-allocation problems

The problem of finding an optimal location frequently occurs in geomarketing, economics and other fields: positioning a new branch of a bank, a supermarket, a fire station, a plant, designing a traffic network, etc. The optimal location of the source facility is the argument-minimum of an optimization problem parametrized by some characteristics of the clients. The random nature of some of these characteristics has already been recognized, but few stochastic models for location-allocation problems address the issue of uncertainty of the locations of the clients, and even then they do it with very naive tools. It is proposed to recognize uncertainty in the spatial positions of the clients, and possible spatial autocorrelation as well, by considering the random inputs of the optimization as one realization of a spatial marked point process. The method, called SPP location-allocation, involves fitting a point process model, simulating from the adjusted process, and solving a family of optimization problems for each simulated set of observations. The advantage of this approach over the deterministic one is twofold: it gives an indication of the spatial variability of the optimal solution, and it allows one to solve larger problems. Finally an application to the optimal positioning of a new fire station in the Toulouse area (France) is presented with some heuristic algorithms.     

A decision support system for fisheries management using operations research and systems science approach

In this paper, we present a general framework, using a systems science approach, for developing a decision support system (DSS) for fisheries management. Decision support systems are quantitative tools for managers to evaluate outcomes of their policies prior to implementation. Our fishery model considers multiple stocks and fisheries simultaneously in balancing catch among targeted and protected fish abundances. Since in the Northeastern US multispecies fishery the distribution of abundance, catch-per-unit-effort and bycatch vary geographically, we focus on a spatial management approach to address their spatial variability. The core component of this DSS applies operations research techniques of simulation and optimization to determine the optimal inter-annual and intra-annual fishing plans in terms of fishing efforts in each sub-area and the time period. The result is the recommended amount to catch from each fish species at each sub-area at any time period so that while management objectives for sustainability of fish stocks are satisfied, the value of landings is maximized. The graphical user interface of the proposed DSS helps users to define inputs, to set constraints and sub-area boundaries, and to visualize the outcomes.     

Synthesis and optimization of the recovery route for residual products under uncertain product demand

The present work describes an optimization model for managing the recovery of residual products that originate at industrial plants. The framework for the proposed general network superstructure, where all possible process transformations, storage, transports and auxiliary operations are accounted for, is modeled using a maximal state task network representation. This framework is combined with the evaluation of a set of environmental impacts, quantified by metrics (for air, water pollution, etc.) through the minimum environment impact analysis methodology and is associated with waste generation at utility production and transportation levels. The final model is described as a mixed-integer linear programming model, which, once solved, is able to suggest the optimal processing and transport routes, while optimizing a given objective function and meeting design and environmental constraints. For each solution obtained, a stochastic flexibility index is computed, allowing for the drawing of trade-off curves for investment decision support.     

Developing a group decision support system based on fuzzy information axiom

Information axiom, one of two axioms of axiomatic design methodology which is proposed to improve a design, is used to select the best design among proposed designs. In the literature, there are a lot of studies related to using of information axiom for the solution of decision making problems. Moreover, applications of information axiom have been increasing day by day. However, calculation procedure of information axiom is not only incommodious but also difficult for decision makers. In this paper, a decision support system (DSS) based on fuzzy information axiom (FIA) is developed in order to make this decision procedure easy. The developed system consists of a knowledge base module including facts and rules, inference engine module including FIA and aggregation method, and a user interface module including entrance windows. The main aim of this study is to present a DSS tool to help the decision makers to solve their decision problems by modifying data-base of the program. In this paper, an application procedure will be presented based on the optimal selection of location for emergency service to illustrate the implementation procedure of the proposed model.     

Decision support or support for situated choice: lessons for system design from effective manual systems

In a number of organisational settings where work is highly skilled but substantially routine, certain entrenched manual systems have resisted digitisation. These systems include card-based systems in emergency despatch, the paper flight progress strips system used in air traffic control, the Kanban system and whiteboard systems used in hospital wards. Research to understand or replace these systems has frequently regarded them as decision support systems (DSS). We report here a detailed case study of a manual whiteboard-based bed allocation system in the ICU of a large general hospital, which shows that the support it provides for users’ action choices cannot be validly conceived as decision support. This system and other effective manual systems may be better understood as a ‘situated choice support system’ (SCSS). Whereas DSS provide actors with a model of the action environment in order to support reasoning about the consequences of alternative actions, SCSS provide actors with structured work environments that reduce possible actions and cue-providing information resources to support a reactive choice between these limited alternatives. The findings warn of the danger of uncritically applying the DSS design paradigm to supporting action choice in skilled routine work, and provide an alternative design theory, which can potentially inform new ICT-based designs.     

一个新的支持多学科模型集成的流域决策支持系统框架研究

传统流域决策支持系统往往使用一两个模型来解决某些特定目标,限于系统结构而不能综合考虑多领域问题。提出了一种新的支持多学科模型集成的流域决策支持系统原型,在一个系统中实现多种学科模型的跨时空尺度集成,为流域综合管理提供全面科学支持。系统采用开放式多学科模型管理方法,其脚本扩展机制使得系统可以容纳几乎所有模型,模型因子方法使得形式多样的科学模型模拟结果可以应用到决策方法中,使系统在多学科模型支持下提供科学合理的决策方案。情景驱动的决策流程、向导式交互界面及GIS等图形化工具支持使得系统用户界面友好\,易用性强。     

A web DSS approach to building an intelligent internet shopping mall by integrating virtual reality and avatar

This paper is concerned with designing and implementing the Internet shopping mall by using a virtual reality-driven avatar and web decision support system (Web DSS). Traditionally, the Internet shopping mall has been designed based on the combination of several hyperlinks, images, and texts. However, this sort of approach results in a lower performance because possible customers cannot make accurate shopping decisions. To overcome these kinds of pitfalls facing the current Internet shopping malls, we propose using a combination of virtual reality and Web DSS. The main virtues of our proposed approach to designing the Internet shopping mall are as follows: First, the virtual reality technique is emerging as one of the alternatives that guarantee a sense of reality for the customers' part and facilitating the complex process of shopping decision makings. Especially, the avatar, which is an artificially designed man working on the Internet, can make the Internet shopping-related decision making processes easier. Second, the Web DSS approach can provide an effective decision support mechanism for customers. Especially, we design a set of intelligent agents for the proposed Web DSS. Experimental results with an illustrative example showed that our proposed approach can yield a new Internet shopping mall paradigm with which customers can benefit from a high level of decision support functions.     

Decision support for flight re-routing in Europe

Congestion has plagued air traffic in the US and in Europe for the last 20 years. To protect air traffic control from overloads, air traffic flow management tries to anticipate and prevent overloads and to limit resulting delays. This paper focuses on understanding the requirements for developing re-routing decision support systems (DSS). It identifies participants in re-routing decisions and investigates the concept of, and need for, a re-routing decision support system. A re-routing demonstrator is discussed as a first step in the development of a DSS and a demonstrator for pre-tactical and tactical re-routings is described. User feedback is presented and issues of automation and complexity of re-routing DSS are discussed. Finally, the integration of re-routing DSS in future air traffic management systems is addressed.     

Applying machine learning to model management in decision support systems

Model management systems have become increasingly important in handling complicated decision problems in decision support systems (DSS). Aiming at overcoming the weaknesses of currently used model management systems, we present a new framework of model management system which is capable of performing model manipulation more effectively. The new approach incorporates machine learning to acquire model manipulation knowledge, stored in the form of schemata, and to refine these acquired schemata. In addition, we also address two issues that have so far been overlooked in the DSS literature: (1) to refine existing model representations as more experiences are accumulated and (2) to create model selection heuristics adaptive to the DSS environment.     

基于次协调逻辑的空战决策支持系统研究

为了解决传统逻辑推理在引入两个相互矛盾的事实时,推理将停止,继而提供不出有价值的结论的问题,给出了基于次协调逻辑理论的一种推理方法.在此基础上构造了次协调逻辑辅助推理空战决策支持系统,在传统逻辑推理因矛盾停止时,启动次协调推理,使得空战决策支持能够在矛盾中求协调,避免了系统陷入平庸状态.在某型空战模拟器上使用取得了初步成效,从仿真结果看具有次协调逻辑辅助推理的空战决策支持系统对复杂的空战环境具有良好的适应性.     

A decision support system for design of mass production machining lines composed of stations with rotary or mobile table

This paper describes a decision support system (DSS) developed in order to offer to machining line designers a cognitive aid for early design stages. The aim of DSS is to assist the decision makers in finding the configuration of a new line that will meet quality and productivity requirements and minimize the investment costs. The current version of DSS is oriented to design of mass production machining lines composed of machines with rotary or mobile tables. This decision support system is based on mathematical models and methods which were devised to provide the designers with the optimal parameters of new line configuration including the required number of working stations of different types, the number of working positions at each station and spindle heads at each working position. The system is implemented under Autodesk Inventor and includes the modules for part modeling, process planning and machining system configuration. Its modular character and open architecture make upgrading with new mathematical tools suitable for other machining systems easy and fast. Moreover, it can be employed either as a separate software or integrated in a Product Life-cycle Management (PLM) tool.     

Intermediating user-DSS interaction with autonomous agents

The use of advanced decision support system (DSS) capabilities is hampered by the inadequacy of a "toolbox" organization of DSS from the user's perspective. In such a setup, the user is assumed to have all the knowledge and skills necessary to appropriately use the tools provided by the system in the decision-making process. This paper proposes a model for the use of autonomous agents as intermediaries between the users and the system. The model is organized around the human problem-solving process. The paper elaborates on the types of intermediary agents and the architecture for a DSS. The approach is illustrated using the prototype for an investment DSS.     

Composite decision support by combining cost-benefit and multi-criteria decision analysis

This paper concerns composite decision support based on combining cost-benefit analysis (CBA) with multi-criteria decision analysis (MCDA) for the assessment of economic as well as strategic impacts within transport projects. Specifically a composite model for assessment (COSIMA) is presented as a decision support system (DSS). This COSIMA DSS ensures that the assessment is conducted in a systematic, transparent and explicit way. The modelling principles presented are illuminated with a case study concerning a complex decision problem. The outcome demonstrates the approach as a valuable DSS, and it is concluded that appraisals of large transport projects can be effectively supported using a combination of CBA and MCDA. Finally, perspectives of the future modelling work are given.     

基于非线性规划协同进化遗传算法的防空导弹火力优化分配研究

为了进一步提高防空导弹目标分配问题的求解效率和解算能力,建立了防空导弹目标火力分配模型,提出了一种非线性规划协同进化遗传算法(NLPCGA).该算法是综合非线性规划算法(NLPA)局部搜索能力强和协同进化算法(CA)求解质量高的优点,并利用遗传理论提高算法的求解效率.通过结合实例,仿真结果表明NLPCGA算法在求解防空目标火力分配问题上要优于单独两种智能算法,可以有效快速地找到最优火力分配方案,为防空作战指挥决策提供支持.     

Optimizing time limits for maximum sales response in Internet shopping promotions

Sellers usually set a promotional time limit to ensure that products can be sold as soon as possible in Internet markets. This research attempts to build a decision support system that optimizes the time limit for maximum sales response or profit in Internet shopping promotions. We decompose the effect of time limits into two opposing forces, which are the awareness and urgency of a promotional offer that are depicted as hyperbolic S-shaped functions. Using the decision calculus approach, we can determine the optimal promotional time limit with different input parameters. We illustrate the use of the proposed system with real world examples and conduct some sensitivity analyses. We compare our numerical results from hyperbolic functions with those from simple exponential functions; we find that hyperbolic functions yield more appropriate promotional time limits on Internet. This research contributes to the field of decision support by providing a new approach to determining the optimal time limit for online sales promotions.     

基于Agent的智能决策支持系统

根据决策支持系统应用中存在的问题,提出了一种新的利用决策支持系统求解问题的思路,并将Agent思想和技术引入到这一思路的实现中,设计了一种基于Agent的智能决策支持系统的架构,该架构主要由模型选择Agent、模型构造Agent、模型求解Agent和人机交互Agent 4个部分组成。该结构的实现可有效地突破基于模型的决策支持系统在求解问题时难以适应动态环境变化的障碍,使决策支持系统真正成为面向问题系统,极大地提高了决策支持系统的智能型,能够根据问题的变化作出适应性的自主的调整,满足用户的求解问题的要求。     

A new approach to water quality modelling and environmental decision support systems

The concepts and technology of environmental decision support systems (EDSS) have developed considerably over recent decades, although core concepts such as flexibility and adaptability within a changing decision environment remain paramount. Much recent EDSS theory has focussed on model integration and re-use in decision support system (DSS) tools and for design and construction of ‘DSS generators’. Many current specific DSS have architectures, tools, models and operational characteristics that are either fixed or difficult to change in the face of changing management needs. This paper reports on development and deployment of an EDSS that encompasses a new approach to DSS tools, generators and specific DSS applications. The system, named E2, is built upon a conceptualisation of terrestrial and aquatic environmental systems that has resulted in a robust and flexible system architecture. The architecture provides a set of base classes to represent fundamental concepts, and which can be instantiated and combined to form DSS generators of varying complexity. A DSS generator is described within which system users are able to select and link models, data, analysis tools and reporting tools to create specific DSS for particular problems, and for which new models and tools can be created and, through software reflection (introspection), discovered to provide expanded capability where required. This system offers a new approach within which environmental systems can be described in the form of specific DSS at a scale and level of complexity suited to the problems and needs of decision makers.     

A decision support system for the technical sustainability assessment of water distribution systems

The purpose of this study is to develop a decision support system (DSS) for the technical sustainability assessment of water distribution systems (WDSs). The technical sustainability is assessed based on the sustainability index methodology using reliability, resiliency, and vulnerability as performance criteria. These performance criteria are visualized by the DSS combining several visualization techniques to improve the raw data readability and the effectiveness of the decision-making process. The technical sustainability of the existing WDS is assessed using the sustainability index methodology and two alternative scenarios are proposed to improve the sustainability. The “new pump” scenario is based on adding network components. The second scenario is based on using reclaimed water for non-potable water demand and fire flow. The results show that the DSS is effective to illustrate time-dependent variables in the WDS and that the sustainability index methodology is a credible approach to compare scenarios and to identify problematic locations.