A Web-Based Decision Support System for the Multiple Capacitated Facility Location Problem

The multiple facility location problem (MFLP) is to locate certain facilities so as to serve optimally a given set of customers, whose locations and requirements are known. When the facility locations have to be selected from a given set of candidate locations, the corresponding location problem becomes a discrete multiple facility location problem (DMFLP). In this study we consider a special case of DMFLP where multiple facilities that are of different type are to be placed (location decision) and assign customers to these facilities (allocation or assignment). The case will be discussed based on with and without interactions among new facilities. We then propose new heuristic solution methods and branch-and-bound algorithms. Computational results on randomly generated data in comparison with optimal solutions indicate that the new methods are both accurate and efficient.

A Web-based real-time decision support system, connecting nine plants to a central information server, was implemented at a large oil and gas facility information centre in the Middle East. The case study presented shows how a real-time decision support system improved profitability. The implementation included a full well accounting package, allowing operators, engineers, petroleum engineers, and accountants to direct production and well properties, access test separator results, and reconcile production with the individual well settings. Qatar Petroleum chose Matrikon's ProcessNet as their Web-based decision support system, as it allowed them to retain their existing and proven business processes while enabling these processes through open connectivity, accessibility, and easy usability. By sharing and distributing information between the business processes and providing this information in single views, efficiency was greatly improved. Introduction Decisions at any corporation are made at a level which is usually applicable, but sometimes not pertinent, to the problem at hand. This situation comes about when all the information is not available to the key decision makers. An example is that of an operator, who might adjust process parameters beyond normal operation limits to address an issue caused upstream by changed feed-stock properties. This might put the product off-spec, whereas the feed-stock was purposely changed elsewhere to improve product quality. This illustrates the need for access to applicable information at every level in the plant. The operator should be able to view the feed-stock properties in the control room, and production staff should be able to analyse process conditions based on feed-stock properties to prevent future upsets. Whether made at the correct level or not, both long-term and short-term decisions are based on available information "processed" through experience or by analysis. Decisions based on experience are in danger of being biased or conservative, while decisions made by analysis could be misguided due to bad quality of data. An objective, fast, and reliable decision-making process requires timely and quality data, distributed to the correct levels in the corporation. The core technology implemented for the needed decision support system should allow the corporation to keep existing information- gathering infrastructure (i.e., process data in various forms, real-time and historian-based) and the long-time proven business processes (i.e., accounting data), while providing access to this information to the entire corporation, if desired. The barrier need no longer exist between plant process data, sales, supply chain, accounting, and management data. The project included configuration of many different and consolidated views, often comprised of Key Performance Indicators (KPIs) specific to the user's needs and job functions. Enabled with secured Web access, engineers can review the plant's performance while away from the site. At the same time, this engineer can query the maintenance database to check the last time a compressor was serviced, and correlate that to the current run-time of the compressor and its current power consumption. Discussion The following is a brief discussion of the base technology, followed by the details of the specific deployment at Qatar Petroleum, and how the project improved the decision-making processes on site.

This chapter elaborates the basic concepts underlying the development of Web-based decision support systems (DSS) with a discussion on the key concepts and technical issues. The utility of Web-based decision support system in enhancing communication and decision-making capability in a distributed environment or a multiple stakeholder process (MSP) has been explained through examples with diverse application from the real world. Further, the chapter introduces a Web-based decision support system developed by the authors for water resources management on basin scale and also some evolving concepts like mobile agent technology to meet the challenges and problems associated with traditional Web-based DSS. The authors hope that better understanding of the key issues and concepts can bring together analysts, modelers, and the end users to build Web-based DSS that are understandable, accessible and acceptable to all, be it corporate or business houses, environmental agencies or government organizations.

The multiple obnoxious facilities location problem is an extremely non-convex optimization problem with millions of local optima. It is a very challenging problem. We improved the best known solution for 33 out of 76 test instances. We believe that the results of many instances reported here are still not optimal and thus better objective function values exist. We challenge the optimization community to design procedures that will further improve some of the results reported here. Optimality can be proven for a small number of new facilities. Proving optimality for a large number of facilities would be an achievement.

Background: Dealing with the consequences of Thailand’s ageing population is a significant challenge. The growing usage of Information and Communication Technology (ICT) has the potential to support healthy and active ageing. Objective: This study aimed to develop a web-based Decision Support System (DSS) and evaluate its usability. Materials and methods: Research and Development (R&D) was a study design. It was divided into two phases: the development of the web-based DSS and its usability. Results: The web-based DSS was designed under the requirements of the users and comprised seven components: 1) the login page; 2) the main page; 3) the register page; 4) active ageing measurement; 5) decision-making for older people; 6) the Occupational Therapy (OT) recommendations system; and 7) exporting information. A System Usability Score (SUS) of 80.41 in the usability test showed that the web-based DSS was very user-friendly and had excellent efficacy, efficiency, and satisfaction. Conclusion: The web-based DSS effectively enhanced ageing for older people.

A SDSS combines database storage technologies, geographic information systems (GIS) and decision modeling into tools which can be used to address a wide variety of decision support areas (Eklund, Kirkby, and Pollitt, 1996). Recently, various emerging technologies in computer hardware and software such as speedy microprocessors, gigabit network connections, fast internet mapping servers along with Web-based technologies like extensible markup language (XML), Web services, etc provide promising opportunities to take the traditional spatial decision support systems one step further to provide easy-to-use, round-the-clock access to spatial data and decision support over the Web. Traditional DSS and Web-based spatial DSS can be further improved by integrating expert knowledge and utilizing intelligent software components (such as expert systems and intelligent agents) to emulate the human intelligence and decision making. These kinds of decision support systems are classified as intelligent decision support systems. The objective of this chapter is to discuss the development of an intelligent web-based spatial decision support system and demonstrate it with a case study for planning snow removal operations.

The growing number of crisis situations around the world in recent years has highlighted the urgent need to improve the capability of Emergency Response Systems. When an emergency happens, the most important response is to promptly evacuate victims or potential victims from dangerous areas to safe places. The use of decision support systems can not only improve the efficiency of evacuation but also reduce losses on life and property. But existing computer-based decision support systems mainly aim at simplifying the evacuation process. The evacuation plans produced by them are difficult to follow and Emergency Response Personnel (ERP) cannot readily access emergency evacuation information in real time. In this paper, we present Blue Arrow, a web-based spatially-enabled decision support system for emergency evacuation planning. Based on their specific requirements, ERP can use the Blue Arrow System to generate various evacuation plans that have intuitive turn-by-turn instructions. These evacuation plans depend not only on the spatial information, but also on the underlying road network information. The Blue Arrow System implements different evacuation plans using the different variants of CCRP algorithm that focus on optimizing various aspects of the evacuation planning process including evacuation time and capacity.

Multiple Sclerosis (MS) is a common neurological disorder in recent years. The diagnosis process of the disease starts with the accurate and precise detection of lesions from MR images. In addition, important achievements are achieved with computer aided decision support systems, which are used as an auxiliary secondary tool in the detection of MS. In this study, we present a web-based decision support system (DeepMSWeb) developed via deep learning for the detection of MS lesions on a publicly-available dataset. Mask R-CNN architecture, one of the deep learning models, is used in the infrastructure of DeepMSWeb, and the developed web application has a flexible and user-friendly interface. In addition, experimental studies are carried out with DeepMSWeb on the dataset consisting of MR images for the detection of MS lesions, and the detection accuracy of the application is supported by similarity measurement metrics. Radiologists who have experienced DeepMsWeb are confirmed that DeepMSWeb can be used as a decision support system for the detection of MS lesions. In addition, it is evaluated that DeepMs Web can be used in different screen sizes, is easy to use and is a fast as decision support tool.

A web-based Decision Support System WebOptim for solving multiple objective optimization problems is presented. The system WebOptim is designed in a modular principle, extensively using XML as communication standard and web services. Its basic characteristics are: user-independent, multisolver-admissibility, method-independent, heterogeneity, web-accessibility. Core system module is an original generalized interactive scalarizing method. It incorporates a number of thirteen interactive methods. Most of the known scalarizing approaches (reference point approach, reference direction approach, classification approach etc.) are realized in this method. The Decision Maker (DM) can choose the most suitable for him/her form for setting his/her preferences: objective weights, aspiration levels, aspiration directions, aspiration intervals. This information could be changed interactively by the DM during the solution process. Depending on the DM's preferences form the suitable scalarizing method is chosen automatically. The chapter begins with an overview of Decision Support Systems (DSS). Examples of DSSs and their applications are discussed.

A web-based open-source decision support system (DSS) was developed to facilitate real-world engagement with dam-operating agencies in the decision-making process involving atmospheric modeling, hydrologic modeling, and web technology. The development process was decoupled into the container (frontend) and the modeling framework for the content (backend), to arrive at an intelligent system that improves the productivity and independent reuse of each component. The backend framework uses the weather forecasts from Numerical Weather Prediction models, downscales to a finer resolution, and simulates hydrologic and data-based artificial neural network models to optimize operations. The frontend architecture disseminates the forecasted meteorological variables, reservoir inflow, optimized operations, and retrospective weekly assessment of forecasts and hydropower benefits. The framework is automated and operationalized over the Detroit dam (Oregon) to generate the daily optimized release decisions. However, backend scripts and frontend elements are flexible and customizable enough that the DSS can be reproduced for other dams. The optimization of reservoir operations based on weather forecasts results in significant additional hydropower benefit without compromising other objectives when compared to the conventional operations. More importantly, the platform helps visualize for the dam operator how much more ‘smarter’ operations can be if weather forecasts and open-source technology are used.

Building Information Modelling (BIM) is a revolutionary technology and process which has led to new ways of thinking and working in construction project delivery. Governments around the world are promoting BIM capacity to eliminate waste on public projects and even mandating its use as part of the reform of the public construction sector and cost-saving strategy. In the UK, the government has declared that no public projects can be accepted without using BIM by 2016. Evidence shows that BIM adoption among small and medium sized enterprises (SMEs) is currently lagging behind and they are losing out in wining publicly funded projects. There are existing sets of frameworks and matrixes developed to assist BIM implementation. However, guidance and frameworks for SMEs are lacking at the present time. This paper reports on criteria and framework as a part of an ongoing study that seeks to develop a web-based Decision Support System (DSS) to assist SMEs to broker risks and rewards of adopting BIM in project delivery. The paper presents the framework and its criteria of the proposed DSS assists SMEs to make informed decisions about whether or not use BIM to deliver building projects, according to specific criteria and queries. This includes tradeoff risks and rewards, broken down into several criteria such as BIM readiness, involvement stage, project value, funding and procurement route.

In this paper we address the multiple obnoxious facility location problem. In this problem p facilities need to be spread within the unit square in such a way that they are far enough from each other and that their minimal distance from n communities, with known positions within the unit square, is maximized. The problem has a combinatorial component, related to the key observation made in Drezner (Omega 87:105–116, 2019) about the role played by Voronoi points. We propose a new approach, which exploits both the combinatorial component of the problem and, through continuous local optimizations, also its continuous component. We also propose techniques to limit the impact on computation times of the number n of communities. The approach turns out to be quite competitive and is able to return 24 new best known solutions with respect to the best results reported in Kalczynski (Optim Lett 16:1153–1166, 2022).

Gold Coast Water is responsible for the management of the water, recycled water and wastewater assets of the City of the Gold Coast on Australia's east coast. Excess treated recycled water is released at the Gold Coast Seaway, a man-made channel connecting the Broadwater Estuary with the Pacific Ocean, on an outgoing tide in order for the recycled water to be dispersed before the tide changes and re-enters the Broadwater estuary. Rapid population growth has placed increasing demands on the city's recycled water release system and an investigation of the capacity of the Broadwater to assimilate a greater volume of recycled water over a longer release period was undertaken in 2007. As an outcome, Gold Coast Water was granted an extension of the existing release licence from 10.5 hours per day to 13.3 hours per day from the Coombabah wastewater treatment plant (WWTP). The Seaway SmartRelease Project has been designed to optimise the release of the recycled water from the Coombabah WWTP in order to minimise the impact to the receiving estuarine water quality and maximise the cost efficiency of pumping. In order achieve this; an optimisation study that involves intensive hydrodynamic and water quality monitoring, numerical modelling and a web-based decision support system is underway. An intensive monitoring campaign provided information on water levels, currents, winds, waves, nutrients and bacterial levels within the Broadwater. This data was then used to calibrate and verify numerical models using the MIKE by DHI suite of software. The Decision Support System will then collect continually measured data such as water levels, interact with the WWTP SCADA system, run the numerical models and provide the optimal time window to release the required amount of recycled water from the WWTP within the licence specifications.

Web-based spatial decision support system for optimum route to forest fires: A case of Viphya plantations

PT. Sinar Indrapura Anugerah Khatulistiwa is a company that operates in the gas sales sector and hires 30 employees every year. Based on the results of the interview, this company agreed to use a decision support system to support the employee recruitment process to avoid subjective factors that are detrimental to job seekers and the company. The decision support system will be built using the MOORA method because this method has a simple and easy to understand concept and provides precise and accurate results to support decision making, is easy to implement and has a high level of sensitivity to the attributes used compared to other methods. The criteria that are considered appropriate are the criteria to support the employee recruitment decision support system at PT. Sinar Indrapura Anugerah Khatulistiwa is education level, age, work experience, health, written test scores and interview scores. This research is expected to be able to design and implement a web-based employee recruitment decision support system using the MOORA method. As a result, the system was successfully designed and implemented on a web basis using the MOORA method with the results of manual calculations matching the calculation results of the system with an accuracy level of 100% so that the system was declared suitable for use as a decision support system for employee recruitment and all of its functionality was running 100%. Keywords: Decision Support System, Employee Recruitment, MOORA Method, Web