scholarly journals DECISION SUPPORT SYSTEM FOR SOLVING THE STREET ROUTING PROBLEM

Transport ◽  
2008 ◽  
Vol 23 (3) ◽  
pp. 230-235 ◽  
Author(s):  
Peter Matis
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Geographical Information Systems ◽  
Support Systems ◽  
Optimal Solution ◽  
Real Data ◽  
Geographical Information ◽  
Routing Problem ◽  
Time Required ◽  
Number Of Customers

Servicing a large number of customers in a city zone is often a considerable part of many logistics chains. The capacity of one delivery vehicle is limited, but, at the same time, it usually serves plenty of customers. This problem is often called a Street Routing Problem (SRP). Key differences between Vehicle Routing Problem (VRP) and SRP are presented here. The main problem of SRP is that when the number of customers is huge, the number of delivery path combinations becomes enormous. As the experimental results show in the case of SRP the error on the length of delivery routes based on an expert's judgment when compared to the optimal solution is in the range of 10–25%. As presented in the paper, only using decision support systems such as Geographical Information Systems (GIS) makes possible to effectively manage SRP. Besides classical measurements used in VRP, such as total length of routes or time required for delivery in each route, other measurements, mostly qualitative ones, are presented. All of these are named as visual attractiveness. This paper discusses possible relationships between quantitative and qualitative measurements that give a promise for finding better solutions of SRP. Several new types of heuristics for solving SRP are evaluated and afterward compared using the real data. One of the key properties of GIS to use routing software is its flexible interactive and user‐friendly environment. Routing software can find a good solution and explore the possibilities while an expert later can change the calculated routes to explore other possibilities based on the expert's judgment. This paper presents a practical use of new heuristics with the ArcView and solution of address mail for several cities in Slovakia served by Slovak Post ltd. Other Decision Support Systems that solve SRP are presented as TRANSCAD developed by Caliper Corporation or GeoRoute promoted by Canadian Post and GIRO.

GEOGRAPHICAL INFORMATION SYSTEMS AND EXPERT SYSTEMS FOR IMPACT ASSESSMENT Part II: Expert Systems and Decision Support Systems

2000 ◽  
Vol 02 (03) ◽  
pp. 415-448 ◽  
Author(s):  
AGUSTIN RODRIGUEZ-BACHILLER
Keyword(s):  
Decision Support ◽  
Information Systems ◽  
Expert Systems ◽  
Impact Assessment ◽  
Decision Support Systems ◽  
Geographical Information Systems ◽  
Support Systems ◽  
Geographical Information ◽  
Environmental Prediction ◽  
User Friendly

This paper and another one preceding it investigate the potential of computer technologies like Geographical Information Systems (GIS) and Expert Systems (ES) to help with Impact Assessment (IA), suggesting that one way to optimise the effectiveness of GIS is to embed these systems in a more user-friendly environment. This paper explores the experience and potential of ES to provide such decision support environment, extending the argument further into the realm of Decision Support Systems (DSS). The proposition behind this paper is that these areas (IA, GIS, ES and maybe DSS) are potentially complementary and there can be mutual benefits if they are brought together. Certain tasks in IA — like screening, scoping, or statement review — already have potential for substantial automation, as an opportunity for technology transfer within organisations involved with IA, so that relatively scarce experts can be freed up for more difficult jobs while less expert staff are promoted to answer more sophisticated questions like these. More technical tasks like impact and environmental prediction also show scope for some degree of modelling-based automation, while other less routinised and more open-ended tasks involved with the management of the whole IA process probably lend themselves better to automation of a different kind, which works more as an "aid" than a substitute for the expert, for which the more flexible DSS seem more appropriate.

scholarly journals Decision Support Systems for Smarter and Sustainable Logistics of Construction Sites

2019 ◽  
Vol 11 (10) ◽  
pp. 2762 ◽  
Author(s):  
Cindy Guerlain ◽  
Samuel Renault ◽  
Francesco Ferrero ◽  
Sébastien Faye
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Urban Areas ◽  
Building Materials ◽  
Support Systems ◽  
Decision Makers ◽  
Geographical Information ◽  
Public And Private ◽  
The Impact

Efficient logistics in urban areas is crucial for construction companies since building materials account for 30–40% of all construction costs and the space on site is highly constrained. To face these challenges, actions coming from both public and private decision-makers to find more sustainable solutions related to the distribution of building materials in urban areas become urgent. Although barely used in such contexts, can decision support systems be of support, and for who and for which purpose? This paper proposes a set of decision support systems addressing public and private decision-makers to improve the construction logistics and supply chain with evidence-based decision-making mechanisms. Those systems are, in particular, a public participatory geographical information system for determining the impact of policy measures, a consolidation center locator, a consolidation center planner, and an innovation measures selector. The paper explains how these decision support systems are settled and experimented from the analysis of pilot sites in European cities and in collaboration with the companies. Our diverse experiments demonstrate that data-driven decision-making is worth it to trigger thought on improvement measures for construction freight transport in urban area. We conclude that additional attention should be devoted to this specific sector.

scholarly journals MODEL LOGIKA FUZZY SUGENO BERBASIS WEB UNTUK SELEKSI PENERIMA BEASISWA

2018 ◽  
Vol 16 (1) ◽  
pp. 25
Author(s):  
Heru Supriyono, Achmad Kurnianto, Muhammad Fikri Khaid, Sujalwo
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
System Development ◽  
Real Data ◽  
Personal Factors ◽  
Web Based ◽  
Grade Point ◽  
Traditional System ◽  
Sugeno Model

One of the main problems emerging in the decision making process by human is the possibilities of bias decision caused by personal factors. This paper discusses the development of a Fuzzy Sugeno based decision support systems for selecting scholarship recipients which is implemented in a web based systems. The main objectives of the research are to result a Fuzzy Sugeno model which mimic human reasoning in the scholarship selection and to calculate recommendation value of every applicant. There are five factors used in the computation involving grade point average (GPA), parent’s income, number of sibling, organization activities, and achievement. Traditional system development life cycle or waterfall method was used in the system development process. Fuzzy Sugeno model is implemented mainly using Django framework with  Python programming language. The result of the research is the web based decision support systems for selecting scholarship recipient. The blackbox testing of the decision support systems showed that all functions of the systems are functioning well as expected and the validation testing result using real data showed that the validity level I equals to 92.3 %  Keyword: scholarship selection, fuzzy logic Sugeno, decision support systems, expert systems, web-based  systems 

Assigning Value to Clinical Information – A Major Limiting Factor in the Implementation of Decision-Support Systems

1996 ◽  
Vol 35 (01) ◽  
pp. 1-4 ◽  
Author(s):  
F. T. de Dombal
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Clinical Information ◽  
Limiting Factor ◽  
Major Difficulty ◽  
Computer Aided ◽  
Computer Aided Decision

AbstractThis paper deals with a major difficulty and potential limiting factor in present-day decision support - that of assigning precise value to an item (or group of items) of clinical information. Historical determinist descriptive thinking has been challenged by current concepts of uncertainty and probability, but neither view is adequate. Four equations are proposed outlining factors which affect the value of clinical information, which explain some previously puzzling observations concerning decision support. It is suggested that without accommodation of these concepts, computer-aided decision support cannot progress further, but if they can be accommodated in future programs, the implications may be profound.

Architectures for Architects

1993 ◽  
Vol 32 (01) ◽  
pp. 12-13 ◽  
Author(s):  
M. A. Musen
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Design And Development

Abstract:Response to Heathfield HA, Wyatt J. Philosophies for the design and development of clinical decision-support systems. Meth Inform Med 1993; 32: 1-8.

Sign in / Sign up

Export Citation Format

Share Document