Techniques for Intelligent Decision Support Systems
01 Jan 2016-pp 159-183
TL;DR: This chapter will look into knowledge-based systems and genetic algorithms which are both widely intelligent systems applied in the construction industry and both are complex techniques that can optimize and find solutions for problems which standard optimization techniques fail to solve.
Abstract: Techniques for systems that support intelligent decision making are the new way of applying what is called artificial intelligence, which can assist in solving complex problems in program management. They embody human-like techniques to solve problems ranging from planning, scheduling, and optimization to expert decision making that are difficult to solve using standard mathematical modeling, as described in previous chapters. This chapter will look into knowledge-based systems (also called expert systems) and genetic algorithms which are both widely intelligent systems applied in the construction industry. Knowledge-based systems use computer programming to solve problems associated with human reasoning. They are much simpler than other artificial intelligence methods and can be used effectively in program management where many decisions need to be made, and where the logic can be structured and developed into a software program. Knowledge-based systems are described, together with their applications in the construction industry and especially from the viewpoint of program management. These are empty programs which users can apply to solve their unique problems, thus freeing the hand of the user from the programming. Genetic algorithms, however, are complex techniques that can optimize and find solutions for problems which standard optimization techniques fail to solve. They are search algorithms that mimic the way evolution has progressed by creating a never-ending supply of better generations.
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TL;DR: The proposed study presents a decision support system to deal with big data and scientific programming for the Industrial Internet of Things and has used the tool of SuperDecisions to plot the hierarchy of situations and select the best alternative among the available.
Abstract: Big data is a challenging issue as its volume, shape, and size need to be modified in order to extract important information for a specific purpose. The amount of data is rising with the passage of time. This increase in volume can be a challenging issue to analyze the data for smooth industry and the Internet of things. Several tools, techniques, and mechanisms are available to support the handling and management process of such data. Decision support systems can be one of the important techniques which can support big data in order to make decisions on time. The proposed study presents a decision support system to deal with big data and scientific programming for the Industrial Internet of Things. The study has used the tool of SuperDecisions to plot the hierarchy of situations of big data and scientific programming and to select the best alternative among the available.
11Â citations
26 Nov 2018
TL;DR: In this paper, the authors employed an extant review of the literature, cross-section survey of construction managers of building projects and experts interview in the Middle East to identify and evaluate the influencing of the key performance criteria on selecting construction methods for building projects.
Abstract: There is a lack of an efficient systematic approach to the selection of appropriate construction methods for building projects. Not only various innovative methods are now available, but also established methods may often be adapted inappropriately, without recourse to the necessary scientific foundation of their efficiency. The result is that there is a low level of performance on building projects. This study examines how key performance criteria were used in the selection of construction methods on projects. The study employed an extant review of the literature, cross-section survey of construction managers of building projects and experts interview in the Middle East to identify and evaluate the influencing of the key performance criteria on selecting construction methods for building projects. It emerged from the Pearson Correlation Coefficient and Analytical Hierarchy Process analysis that key performance criteria consisting of time, quality, and cost have strong positive significant roles in the selection of construction methods used on building projects and that these selection criteria differed depending on the building components. The study concludes that the likelihood of a construction method being selected for use on projects in the Middle East depends on its ability to shorten the duration, improving the quality and reduce the cost of projects.
7Â citations
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11 Jul 2012
TL;DR: In this article, a multi-objective elitist Nondominated Sorting Genetic Algorithm (NSGA-II) was developed for solving finance-based scheduling problem of multi-projects with multi-mode activities.
Abstract: Lack of financing and cash deficit is considered as a primary threat to contractor’s financial management. Therefore, in case of insufficient cash, many contractors find it difficult to stick with the project schedule leading to extra overhead costs and liquidated damages. Mainly contractors deal with the project scheduling and financing as two independent functions of construction project management. Thus, the main objective of this research is to develop a multi-objective elitist Nondominated Sorting Genetic Algorithm (NSGA-II) for solving finance-based scheduling problem of multi-projects with multi-mode activities. A CPM scheduling model is constructed with its associated cash flow to calculate the values of the multiple objectives. The problem involves the minimization of conflicting objectives: duration of multiple projects, financing costs, and maximum negative cumulative balance. The designed optimization model performs operations of NSGA-II in three main phases: (1) Population initialization; (2) Fitness evaluation; and (3) Generation evolution. An application example is analyzed to illustrate the use of the model and to demonstrate its capabilities in generating optimum solutions. The model can be considered relevant for practitioners to use in large construction projects to make decisions regarding financing.
10Â citations
TL;DR: A knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project is proposed and described.
Abstract: The appropriate selection of construction methods to be used during the execution of a construction project is a major determinant of high productivity, but sometimes this selection process is performed without the care and the systematic approach that it deserves, bringing negative consequences. This paper proposes a knowledge management approach that will enable the intelligent use of corporate experience and information and help to improve the selection of construction methods for a project. Then a knowledge-based system to support this decision-making process is proposed and described. To define and design the system, semistructured interviews were conducted within three construction companies with the purpose of studying the way that the method' selection process is carried out in practice and the knowledge associated with it. A prototype of a Construction Methods Knowledge System (CMKS) was developed and then validated with construction industry professionals. As a conclusion, the CMKS was perceived as a valuable tool for construction methods' selection, by helping companies to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The described benefits as provided by the system favor a better performance of construction projects.
8Â citations
01 Jan 2008
TL;DR: A GA based model for determination of the best combination of the time, cost, and resources in a multiple resource constraint problem and uses weighted sum method for handling multi-objective optimization problem is presented.
Abstract: Simultaneous optimization of time, cost, and utilized resources in a construction project is vital. This paper presents a GA based model for determination of the best combination of the time, cost, and resources in a multiple resource constraint problem. The proposed model considers both resource allocation and leveling simultaneously. Since the problem is assumed to be resource constraint, resource allocations modify the schedules based on multiple resource restrictions. Besides, the basic concept of resource leveling, minimization of Mx (X-moment of resource histogram) is used to minimize resource fluctuation. In addition to Mx, the paper uses My (Y-moment of resource histogram) in resource leveling process because simultaneous application of them improves it to take into consideration the resource utilization period. The paper uses weighted sum method for handling multi-objective optimization problem. Performance of the model is illustrated using a simple example project.
4Â citations
01 Jan 2012
TL;DR: In this study a genetic algorithm (GA) is developed for the resource levelling problem and it is indicated that the GA outperforms resource levelled heuristic of Microsoft Project 2010 significantly.
Abstract: Critical path method (CPM) is commonly used in scheduling of construction projects. However, CPM only considers the precedence relations between the activities and does not consider resource optimization during scheduling of projects. Optimal allocation of resources can be achieved by resource levelling. Resource levelling is crucial for effective use of construction resources particularly to minimize the project costs. However, commercial scheduling software has very limited capabilities for solving the resource levelling problem. In this study a genetic algorithm (GA) is developed for the resource levelling problem. The performance of GA is compared with the performance of Microsoft Project 2010 for several sample projects. The comparisons indicate that the GA outperforms resource levelling heuristic of Microsoft Project 2010 significantly. Furthermore, exact solutions were obtained for the sample problems using linear-integer programming technique. Exact solutions reveal that the algorithm is capable of achieving adequate solutions. Hence, the GA provides a powerful alternative for the resource levelling problem.
3Â citations