A web-based tool for the development of Intensity Duration Frequency curves under changing climate

Intensity Duration Frequency (IDF) curves are among the most common tools used in water resources management. They are derived from historical rainfall records under the assumption of stationarity. Change of climatic conditions makes the use of historical data for development of IDFs for the future unjustifiable. The IDF_CC, a web based tool, is designed, developed and implemented to allow local water professionals to quickly develop estimates related to the impact of climate change on IDF curves for almost any local rain monitoring station in Canada. The primary objective of the presented work was to standardize the IDF update process and make the results of current research on climate change impacts on IDF curves accessible to everyone. The tool is developed in the form of a decision support system (DSS) and represents an important step in increasing the capacity of Canadian water professionals to respond to the impacts of climate change.     

A multi-objective reliability-based decision support system for incorporating decision maker utilities in the design of infrastructure

Infrastructure comprises the most fundamental facilities and systems serving society. Because infrastructure exists in economic, social, and environmental contexts, all lifecycle phases of such facilities should maximize utility for society, occupants, and designers. However, due to uncertainties associated with the nature of the built environment, the economic, social, and environmental (i.e., triple bottom line) impacts of infrastructure assets must be described as probabilistic. For this reason, optimization models should aim to maximize decision maker utilities with respect to multiple and potentially conflicting probabilistic decision criteria. Although stochastic optimization and multi-objective optimization are well developed in the field of operations research, their intersection (multi-objective optimization under uncertainty) is much less developed and computationally expensive. This article presents a computationally efficient, adaptable, multi-objective decision support system for finding optimal infrastructure design configurations with respect to multiple probabilistic decision criteria and decision maker requirements (utilities). The proposed model utilizes the First Order Reliability Method (FORM) in a systems reliability approach to assess the reliability of alternative infrastructure design configurations with regard to the probabilistic decision criteria and decision maker defined utilities, and prioritizes the decision criteria that require improvement. A pilot implementation is undertaken on a nine-story office building in Los Angeles, California to illustrate the capabilities of the framework. The results of the pilot implementation revealed that “high-performing” design configurations (with higher initial costs and lower failure costs) had a higher probability of meeting the decision maker’s preferences than more traditional, low initial cost configurations. The proposed framework can identify low-impact designs that also maximize decision maker utilities.     

A decision support system for the planning of the workload on a grain terminal

Ships, loaded with agricultural products, are handled by GEM at three different terminals in the port of Rotterdam. Each terminal consists of several berths and has both floating equipment and shore equipment. This paper describes the terminal system, the planning process and a menu driven computer planning model of the system. The planning model is split up into a first phase, in which berths are allocated, and a second phase, in which unloading equipment is assigned. The user of the model has the opportunity to manipulate several penalties and assign preferences to berths.     

Change, attitude to change, and decision support system success

It is generally recognized that user attitudes are important determinants of success in the implementation of information systems. Among these, users' attitudes towards the changes introduced by a system are thought to be especially important in the implementation of MIS and OR/MS applications. Based on the results of a survey of 32 decision support systems (DSS), this study investigates the relationships between the extent of changes caused by the systems to users' work environments, the users' attitudes towards work related changes, and four measures of DSS success. The results indicate that DSS users are more satisfied with, and use more extensively, those DSS that bring change than DSS that do not result in substantial changes to their work environment. Implications for the measurement of DSS success are also discussed.     

New horizons at the core of information systems: decision support system advances

Here, we argue that decision support systems (DSSs) research is a core area of the information systems (IS) discipline, being one of six major expansions that have occurred in the IS field. Interestingly, DSS research is often blended with some other expansions experienced by the IS field: namely, organizational computing, electronic commerce/business, and pervasive computing. The DSS core of IS research continues to grow along ever-widening horizons. Diverse exemplars of such DSS advances are found in the papers of this special issue.     

An analytic hierarchy process and two-sided matching based decision support system for military personnel assignment

Assignment of military personnel to positions is very demanding, primarily a manual process performed by detailers. Detailers try to satisfy needs and preferences of commands and personnel. In this paper, an analytic hierarchy process (AHP) and two sided matching based Decision Support System is proposed to assist detailers. The DSS is programmed to generate positions’ preferences from position requirement profiles and personnel competence profiles by using analytic hierarchy process and matches personnel to positions by using two-sided matching. The use of the proposed DSS is demonstrated with an example. Also, the effects of preference list length on two-sided matching are examined.     

JUDGES: A descriptive group decision support system for the ranking of items

A set of tools for group decision support are presented. Decision problems involving several decision makers, here-after called judges, that have to rank several alternatives, are considered. The toolbox is called JUDGES. It includes the four following procedures:

• - a hierarchical representation of the judges allows to display the existing conflicts between groups of judges,

• - enhanced box-plots representations of the alternatives are generated in order to detect those that are responsible for the major conflicts,

• - specific advice is issued to each judge in order to reach more easily a consensus,

• - a general framework for a pairwise group preference structure is proposed, and can be used to finalise the decision.

These procedures are embedded in an interactive software, implemented on micro-computer, which currently simulates the use on a network. Actual network implementation is foreseen in the near future. Several applications are presented and future developments are discussed.

A decision support system for optimizing dynamic courier routing operations

In this paper, we propose a prototype of a decision support system (DSS) that integrates a hybrid neighborhood search algorithm to solve the offline and online routing problems arising in courier service. In the dynamic operational environment of courier service, new customer orders and order cancellations continually arrive over time and thus disrupt the optimal routing schedule that was originally designed. This calls for the real-time re-optimization of routes. As service level is sensitive to whether allowable service time intervals are wide or narrow, it is valuable to study how adjustable and flexible time windows influence the courier service efficiency in a dynamic environment. To capture these dynamic features, a dynamic vehicle routing problem (DVRP) that simultaneously considers new customer orders and order cancellations is investigated in this study. Meanwhile, fuzzy time windows are formulated in the DVRP model to quantify the service level and explore the service efficiency. To tackle the new problem, we propose a competitive hybrid neighborhood search heuristic for (re)optimizing the offline and online routes. Numerical computational experiments and the comparison with results from Lingo show that our algorithm is capable of re-optimizing dynamic problems effectively and accurately in a very short time. The proposed model and algorithms are able to enhance courier service level without further expense of a longer traveling distance or a larger number of couriers.     

A knowledge-based decision support system for measuring the performance of government real estate investment

This paper describes a knowledge-based decision support system for measuring the performance of government real estate investment using DEA models. We propose an evaluation framework for real estate investment, including a database, a model base, and a knowledge base, to create a tool that a government can use to deal with decision-making problems via the Internet. This decision support system converts numerical data into information that can be used to evaluate possible real estate investments. Particularly, rules in the rule base are explained in more detail for illustrating the process of reasoning and KDSSGREI adapts quickly and accurately to infer and generate suggestions or actions. Data envelopment analysis (DEA) is used to perform efficiency analysis in this paper. Finally, we apply China's case to obtain strategies for reforming real estate investment.     

A decision support system for strategic planning in large-scale marketing channels: An example in the tile industry

This paper presents a decision support system for strategic planning in marketing channels. A dynamic model of the marketing channel is employed which comprises manufacturer and retailer levels. Decision making is achieved through a game theoretical inference mechanism in which each player (manufacturer/retailer) optimises for a long-term profit maximisation objective. Both historical data and managerial expertise are used for the parameterisation of the system's knowledge base. The decision support system provides a forecast of profit and sales and computes pricing and shelf space allocation strategies that maximise long-term profit. It offers facilities such as the study of coalitions, long-term decision-making in all phases of a product's life cycle, the impact of pricing, allocation strategies, production expansion, cost regulation, and others. The operationality of the system is illustrated in decision-making situations in the tile industry.     

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.     

Group decision process support system for regional planning—A perspective from Japan

Regional planning has been regarded as a design activity. Usually planners focus on physical design rather than on societal issues. Nowadays, mass communication, environmental issues and social awareness lead to often complex and conflicting needs and interests of the public in regional planning. This paper focuses on the regional planning as a group problem solving process from the view of information processing. It offers an analysis of the causes of conflicts in the group decision process, and defines the characteristics of group decision process support systems     

A decision support system for automotive product planning and competitive market analysis

A decision support system (DSS) for automotive product marketing, design and manufacturing in China is presented in this paper. The DSS is developed as a tool to support product planning, competitive market analysis, supply chain analysis and subsequent manufacturing systems planning and deployment. The system consists of a number of automotive related databases which provide information about manufacturers' performance in each market segment as well as production information of all existing market players in the Chinese auto industry. Product planning, one of the key modules of the DSS prototype, is highlighted in this paper. It supports decision makers in determining suitable strategies for market entry by analyzing existing competitors' status, growth estimation of each market segment, and competitive market analysis for new vehicle products. A case study for new market entry is included here to demonstrate the feasibility and effectiveness of the proposed methodology.     

A simulation-based decision support system for a multi-echelon inventory problem with service level constraints

In this paper, we present a simulation-based decision support system for solving the multi-echelon constrained inventory problem. The goal is to determine the optimal setting of stocking levels to minimize the total inventory investment costs while satisfying the expected response time targets for each field depot. We derive new decision support algorithms to be applied in different scenarios, including small-sample and large-sample cases. The first case requires that the set of alternative solutions is known at the beginning of the experiment, and the number of evaluated solutions may depend on the simulation budget (i.e., the time available to solve the problem). In the second case, the alternative solutions are generated sequentially during the searching process, and we may terminate the algorithm when the specified sampling budget is exhausted. Empirical studies are conducted to compare the performance of the proposed algorithms with other conventional optimization approaches.     

Development of a decision support system for service delivery

Most traditional service delivery models were developed to solve single objective problems. While the disaster recovery task usually needed the consideration of multiple objectives (e.g. the total waiting time, the total weighted time of travelling, the fairness of resource distribution). Therefore, the traditional models can't completely support the disaster recovery task. In the real world, the assignments of service delivery are always performed by the vehicle dispatchers or truck drivers based on their experiences. However, the intuitive assignment methods are lacking a mathematic basis. They may be efficient but not necessarily effective. In order to provide an efficient and effective decision support system, this study has focused on the general expression of performances for service delivery and modifies the traditional delivery models by rule-inference techniques. The objective of this paper is to describe how a decision support system has been developed to achieve the performance requirement in emergency service delivery tasks, while traditional routing algorithms are modified and software techniques are utilized under a PC-based environment. Furthermore, some directions for future improvement are proposed.     

A decision support system for cyclic master surgery scheduling with multiple objectives

This paper presents a decision support system for cyclic master surgery scheduling and describes the results of an extensive case study applied in a medium-sized Belgian hospital. Three objectives are taken into account when building the master surgery schedule. First of all, the resulting bed occupancy at the hospitalization units should be leveled as much as possible. Second, a particular operating room is best allocated exclusively to one group of surgeons having the same speciality; i.e., operating rooms should be shared as little as possible between different surgeon groups. Third, the master surgery schedule is preferred to be as simple and repetitive as possible, with few changes from week to week. The system relies on mixed integer programming techniques involving the solution of multi-objective linear and quadratic optimization problems, and on a simulated annealing metaheuristic.     

Review of literature on decision support systems for natural hazard risk reduction: Current status and future research directions

Natural hazard risk is largely projected to increase in the future, placing growing responsibility on decision makers to proactively reduce risk. Consequently, decision support systems (DSSs) for natural hazard risk reduction (NHRR) are becoming increasingly important. In order to provide directions for future research in this growing area, a comprehensive classification system for the review of NHRR-DSSs is introduced, including scoping, problem formulation, the analysis framework, user and organisational interaction with the system, user engagement, monitoring and evaluation. A review of 101 papers based on this classification system indicates that most effort has been placed on identifying areas of risk and assessing economic consequences resulting from direct losses. However, less effort has been placed on testing risk-reduction options and considering future changes to risk. Furthermore, there was limited evidence within the reviewed papers on the success of DSSs in practice and whether stakeholders participated in DSS development and use.     

A decision support system for locating VHF/UHF radio jammer systems on the terrain

In this study, a mathematical model is suggested concerning the location of VHF/UHF frequency radio jammer systems to the terrain parts to conduct single frequency or sequential frequency jamming, and then a decision support system (DSS), based on the suggested model, is formed. Location problem is modelled by the maximum covering location problem and LINGO-8 package program is used to solve the model. Interaction with the user is provided via the MS-Excel program in the DSS. In the application part of the study, a scenario was set up and the model was run for the two cases, weighted and equally weighted situations of the targets. With the same scenario, backup positions for the jammer systems were tried to be determined and solutions for the scenario were evaluated.

A human-centred methodology applied to decision support system design and evaluation in a railway network context

This article describes a methodological process for the design and evaluation of an interactive system in an industrial context. The process is called the U-model, and has been used in many projects since the early 1990s. The article describes a recent case study in which the U-model was adapted and used during a project involving the design of a decision support system intended for a railway investment context.