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.
11 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.
7 citations
References
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TL;DR: In this paper, improvements are proposed to resource allocation and leveling heuristics, and the GA technique is used to search for near-optimum solution, considering both aspects simultaneously.
Abstract: Resource allocation and leveling are among the top challenges in project management. Due to the complexity of projects, resource allocation and leveling have been dealt with as two distinct subproblems solved mainly using heuristic procedures that cannot guarantee optimum solutions. In this paper, improvements are proposed to resource allocation and leveling heuristics, and the Genetic Algorithms (GAs) technique is used to search for near-optimum solution, considering both aspects simultaneously. In the improved heuristics, random priorities are introduced into selected tasks and their impact on the schedule is monitored. The GA procedure then searches for an optimum set of tasks' priorities that produces shorter project duration and better-leveled resource profiles. One major advantage of the procedure is its simple applicability within commercial project management software systems to improve their performance. With a widely used system as an example, a macro program is written to automate the GA proced...
374 citations
TL;DR: In this paper, the authors address the problems of risk management in construction projects using a knowledge-based approach, and propose a methodology based on a three-fold arrangement that includes the modeling of the risk management function, its evaluation, and the availability of a best practices model.
134 citations
TL;DR: A multi-objective model for the time-cost trade-off problem in PERT networks with generalized Erlang distributions of activity durations, using a genetic algorithm, and compares the genetic algorithm results against the results of a discrete-time approximation method for solving the original optimal control problem.
96 citations
Book•
01 Apr 1986
TL;DR: This chapter discusses the tools and techniques of artificial intelligence programming environments and the POPLOG system, and the implications of why artificial intelligence needs an empirical foundation.
Abstract: Part 1. Principles of artificial intelligence, John Campbell. Part 2 Tools and techniques: artificial intelligence programming environments and the POPLOG system, John Gibson LISP, lists and pattern-matching, Tony Hasemer. Part 3 Applications: computer processing of natural languages, Alan Ramsay levels of representation in computer speech synthesis and recognition, Stephen Isard computer vision, David Hogg artificial intelligence and robotics, Michael Brady the anatomy of expert systems, Richard Forsyth. Part 4 Frontiers: machine learning, Richard Forsyth memory models of man and machine, Ajit Narayanan. Part 5 Implications: why artificial intelligence needs an empirical foundation, Noel E Sharkey and Gordan D A Brown breaking out of the chinese room, Steve Torrance social implications of artificial intelligence, Derek Partridge.
59 citations
01 Jan 2002
TL;DR: This chapter identifies this relationship and explains how project planning representations called work breakdown structures (WBS) are similar to plan representations employed by hierarchical planners, and applies well-known hierarchical planning techniques to assist a project planner efficiently create WBSs.
Abstract: Project management is a business process for successfully delivering one-of-a kind products and services under real-world time and resource constraints. Developing a project plan, a crucial element of project management, is a difficult task that requires significant experience and expertise. Interestingly, artificial intelligence researchers have developed both mixed-initiative and automated hierarchical planning systems for reducing planning effort and increasing plan evaluation measures. However, they have thus far not been used in project planning, in part because the relationship between project planning and hierarchical planning has not been established, hi this chapter, we identify this relationship and explain how project planning representations called work breakdown structures (WBS) are similar to plan representations employed by hierarchical planners. We exploit this similarity and apply well-known hierarchical planning techniques, including an integrated (case-based) plan retrieval module, to assist a project planner efficiently create WBSs. Our approach uses stored episodes (i.e., cases) of previous project planning experiences to support the development of new plans. We present an architecture for knowledge-based project planning system that implements this approach.
30 citations