Decision Support System to Evaluate and Compare Concession Options

With the increased popularity of concession projects over the last three decades, there is a need for a decision support system (DSS) capable of evaluating and comparing several concession project investment (CPI) options in an effective and efficient manner. Hence, a novel DSS has been developed that takes into consideration both financial and nonfinancial aspects of the investment option, as well as the uncertainties commonly encountered during the feasibility stage of a project. The DSS is fully implemented as a standalone computer software package, ECCO (evaluate and compare concession options), in order to be of practical use. This paper outlines and validates ECCO’s design and structure through the demonstration of its capabilities in the evaluation and comparison of three real-life CPI case studies.     

Neurofuzzy Decision Support System for Efficient Risk Allocation in Public-Private Partnership Infrastructure Projects

The performance of public-private partnership (PPP) infrastructure projects is largely contingent on whether the adopted risk allocation (RA) strategy is efficient. Theoretical frameworks drawing on the transaction cost economics and the resource-based view of organizational capability are able to explain the underlying mechanism but unable to accurately forecast efficient RA strategies. In this paper, a neurofuzzy decision support system (NFDSS) was developed to assist in the RA decision-making process in PPP projects. By combining fuzzy and neural network techniques, a synthesized fuzzy inference system was established and taken as the core component of the NFDSS. Evaluation results show that the NFDSS can forecast efficient RA strategies for PPP infrastructure projects at a highly accurate and effective level. A real PPP infrastructure project is used to demonstrate the NFDSS and its practical significance.     

Web-Based Client Advisory Decision Support System for Design–Builder Prequalification

The design–build procurement route is gaining popularity and being extensively used by many clients. Scrutinizing the capabilities of design–build “candidate” organizations (who submit proposals for prequalification/short listing), is a complex task that demands the evaluation of several quantitative and qualitative attributes. The crucial task of design–builder prequalification needs multidisciplinary expertise that often poses tough challenges to many construction clients. A Hong Kong based cross-sectional research study of various international clients’ design–builder selection approaches unveiled several selection strategies and criteria used; and benchmarked some best practices. Based on such consolidated knowledge, a structured design–builder selection model was developed. The conceptualized frameworks for design–builder prequalification are described in this paper. An overview of the development and preliminary validation of a prototype web-based decision support system for design–builder prequalification is also presented in this paper.     

Using Group Decision Support System to Support Value Management Workshops

A group decision support system (GDSS) is an interactive computer-based information system that combines the capabilities of communication technologies, database technologies, computer technologies, and decision technologies to support the identification, analysis, formulation, evaluation, and solution of semistructured or unstructured problems by a group in a user-friendly computing environment. As there is a strong demand for improvements to the practice of value management (VM), research has been conducted to design a GDSS prototype system, named the interactive value management system (IVMS), to explore its potential application in VM workshops and to investigate the effect of the application. The paper begins with an introduction to the problems of implementing VM in the Hong Kong construction industry and then proceeds to an illustration of the features of the proposed system, which has been developed in the research. Two validation studies designed to test the support of the proposed system are described and the results discussed. Findings from this research indicate that IVMS is supportive in overcoming the problems and difficulties in VM workshops.     

Decision Support System for Manufactured Housing Facility Layout

Productivity improvement of manufactured housing (MH) production systems has been a great concern to manufacturers and production managers. Studies show that a typical manufactured housing plant fails to produce at desired capacity and production rate because of several shortcomings. The evaluation of the production system efficiency in the factory is essential for meeting the growing demand of customers with respect to design and size of the housing product. It is imperative to explore alternative layout designs that would be more efficient and productive. A decision support system (DSS) is proposed to assist the user in selecting an efficient layout design matching specified requirements and business constraints. The DSS framework covers interrelated factors of: (1) the market demand; (2) MH organization; (3) MH production process; and (4) MH production planning and facility design. Existing MH factories can utilize simulation and optimization components of the DSS in streamlining their activities and locating then solving potential bottlenecks. Additionally, the DSS can be used in selecting optimal production system layout for new plant design.     

Simulation-Based Decision Support System for Economical Supply Chain Management of Rebar

The economics of a materials management system is defined by the size of the shipments, the scheduling strategy that allows contractors to handle uncertainty and variability in the supply chain, and the timing of the shipments, which in turn depend on the environment in which the project is taking place. This study presents a simulation-based decision support system to assist contractors in selecting the most economical rebar management system prior to the start of construction by recommending lot sizes (large, small), a scheduling strategy (optimistic, neutral, pessimistic), and buffer sizes (large, medium, small) given the conditions of the project. This model is of benefit to contractors and researchers because it generates the probable cost of inventory of 18 alternative rebar management systems ranging from just in case (JIC) to just in time (JIT) and including different variations in between. It allows contractors to select the alternative with least cost of inventory at the planning stages of a project. The simulation model was tested by using actual data obtained from a trade center project in Istanbul, Turkey. As expected, the test indicated that JIC was the most economical rebar management system in a case study conducted in a developing country, as it generated a savings of 4.8% over JIT.     

Knowledge-Enabled Decision Support System for Routing Urban Utilities

This paper presents a Web-based system for supporting the selection of the most suitable routes for buried urban utilities. The aim of the proposed system is to support (not make) decisions through a collaborative semiautomated environment, in which stakeholders can share information and/or study the impacts of different routing alternatives with respect to decision constraints. First, the knowledge relating to route selection for urban utilities is represented through an ontology. The ontology defines the types and attributes of infrastructure products and the surrounding areas. It also defines the impacts of routing options on surrounding areas through a set of decision criteria adopted to evaluate the effectiveness of any route in terms of its potential impacts. A set of constraints are also defined to help represent/study the decision criteria. Second, a GIS-based system has been created to help visualize route data, interact with users, and support the needed discussions among stakeholders. The portal also achieves data interoperability through wrapping existing geospatial data with ontology structures. Finally, a set of reasoners have been created to help quantify/augment some of the constraints. The system is capable of (1)?extracting the attributes of each routing option, (2)?testing the interaction/conflicts between route attributes and the constraints of the surrounding area, (3)?studying the impacts of a route as stipulated in the ontology, (4)?referring users to existing best practices to help enhance routes or address conflicts and, when needed, (5)?develop objective measures for comparing different routes. On the microlevel (street level), route options are evaluated through a “constraint-satisfaction” approach. On the macrolevel (city level), route options are evaluated through a fuzzy inference scoring system. The proposed system focuses on facility life cycle, sustainability, and community impacts. Construction costing, scheduling, labor, and equipment along with other management issues can either be added to the system or, better, analyzed through integrating the system with four-dimensional (4D) modeling tools.     

Decision Support System for Stakeholder Involvement

Stakeholder involvement is essential to the development of a total maximum daily load (TMDL) and its implementation plan. A tool, beyond a simulation model, is needed to support the decision making process that requires negotiation and compromise among stakeholders. The decision support system (DSS) described herein has a TMDL module to calculate various combinations of point and nonpoint loads that can meet the water quality criteria. Its Consensus module allows stakeholders to formulate, evaluate, modify, and vote for alternatives. The DSS displays bar charts for pollution loads from various subwatersheds and attributes the nonpoint loads to land uses. The water quality consequence of the pollution loads is output in maps, which shows sections meeting criteria in green and those not in red. The DSS requires a front end effort of site specific adaptation and model calibration. An Internet-based stakeholder process was developed to allow more concerned citizens to participate in management decisions.     

Decision Support System for Microtunneling Applications

Microtunneling is a trenchless technology method used for installing new pipelines. The inherent advantages of this method over open-cut trenching have led to its increasing use since its first introduction into North America in the early 1980s. With this technology, surface disruption can be minimized, especially in urban areas, and high accuracy of installation (usually less than 2?cm over 100?m) can be achieved in both line and grade. But microtunneling machines are very expensive and few contractors have extensive experience with this technology. Microtunneling can also be risky when unexpected obstacles or soil changes occur. Careful constructability analysis is needed, and an appropriate microtunneling method should be selected in order to achieve successful completion of microtunneling projects. A computerized decision support system (DSS) for microtunneling was developed to support decision making for contractors who want to bid on microtunneling projects. This paper discusses the decision-making process for microtunneling and the development of the DSS. When the user enters basic information about the potential project such as drive length, installation depth, pipe diameter, and soil condition, the DSS evaluates whether microtunneling will be economically feasible and suggests appropriate types of microtunneling methods. The user can then select microtunneling machines, types of pipes, and types of shaft construction methods. This DSS is most beneficial when used at the preplanning stage by utility contractors.     

Multiagent System for Construction Claims Negotiation

Negotiation is an important aspect of the construction process. Different negotiation theories and models are available and have been deployed in a variety of situations. In some cases, these have been incorporated into multiagent systems that address a number of engineering problems. This paper is concerned with the approach adopted in the development of a multiagent system for construction claims negotiation (MASCOT). It reviews the key negotiation theories, outlines the peculiarities of the domain (construction claims negotiation), and discusses the choice of an appropriate negotiation mechanism for MASCOT. Of particular interest is the integration of Zeuthen’s bargaining model with a Bayesian learning mechanism, which addresses the characteristics of construction claims negotiation. An example is presented to demonstrate the application of the MASCOT model in a real construction claim case.     

Decision Support System for Scheduling Steel Fabrication Projects

One of the most important and difficult problems faced by the steel fabrication industry is the planning and scheduling of shop activities. Competitive pressures force fabricators to disrupt schedules in progress to accommodate frequent requests from key customers for changes in design and/or delivery schedules. Capacity management is a complex problem and is key to proper management of manufacturing/fabrication activities. This paper presents a decision support system for planning and scheduling of steel fabrication projects. Although the immediate application of this approach is steel fabrication, its fundamental heuristic approach can be applied to any construction job shop scheduling exercise. Its main advantage over techniques such as CPM is that it is resource driven; its advantages over simulation techniques are its simplicity and overall schedule development time.     

Decision Support System for Surface Irrigation Design

The SADREG decision support system was developed to help decision makers in the process of design and selection of farm surface irrigation systems to respond to requirements of modernization of surface irrigation—furrow, basin, and border irrigation. It includes a database, simulation models, user-friendly interfaces, and multicriteria analysis models. SADREG is comprised of two components: design and selection. The first component applies database information, and through several simulation and computational tools, produces a set of design alternatives in agreement with the user options. These alternatives are characterized by several hydraulic, economic, and environmental indicators that allow appropriate selection and ranking. The selection component bases upon multicriteria analysis using composite programming and ELECTRE II ranking models, which support the decision maker to select the best alternative. The decision maker participates in all decision processes through a user-friendly interface that allows expressing design options and priorities. SADREG was tested with data collected from field experiments. In addition to describing the modeling approach, an application to a sector of the Lower Mondego Irrigation Project, Portugal, is presented.     

Integrated Decision Support for Roadway Safety Analysis

This paper presents an integrated decision-support framework that helps public agencies identify high-crash locations and develop cost-effective safety improvement projects. State-of-the-art safety concepts, such as safety performance functions, empirical Bayesian method, and potential for safety improvements, are incorporated to identify hazardous highway locations. Cost-effective safety projects are prioritized based on life-cycle safety benefit evaluation and optimal resource allocation models. An efficient solution algorithm to the optimization model is also proposed. The models are implemented in an internet-based, geographic information system (GIS) software tool that builds on state-of-the-art information technologies, graphical interfaces, and customized GIS algorithms such as spatial analysis with buffering operations.     

Predicting the Outcome of Construction Litigation Using Boosted Decision Trees

Construction litigation has become commonplace in numerous construction projects, particularly in large contracts. Miscommunication, inadequate plans and specifications, rigid contracts, changes in site conditions, nonpayment, catch up profits, limitations on manpower, tools, and equipment, improper supervision, notice requirements, constructive changes not recognized as such by owner, delays, and acceleration measures provoke claims and often result in disputes. A boosted decision tree system was used to predict the outcome of construction litigation. The study was conducted by using the same 114 Illinois court cases that were used in earlier prediction studies conducted with artificial neural networks in 1998 and case-based reasoning in 1999, augmented by an additional 18 cases that were filed in 1990–2000. All cases were extracted from the Westlaw on-line service. The best prediction result obtained with boosted decision trees was 90%. The boosted decision tree model appears to be a promising tool to help create a dispute-free construction industry.     

International Expansion Decision for Construction Companies

There exist several reasons for construction firms to expand their business into international markets. But the complex international environment is affected by diverse factors and creates risks that are not well understood by companies that are active mostly in domestic markets. It is therefore essential for construction companies to follow a disciplined and well-informed strategy when deciding whether to enter international markets. Company strengths relative to conducting business in international markets, the threats and opportunities associated with overseas work, and the costs and benefits of undertaking construction projects in specific countries need to be considered in this decision. The interactions between the complex factors can be structured in a model that can help one to make a rational judgment. The International Expansion Decision Model developed in this study is based on the Analytic Hierarchy Process (AHP) improved by the addition of a Delphi survey. The main objective of this research study is to facilitate the entry decision into foreign markets and to highlight the importance of the factors involved in this decision. This study is of relevance to practitioners as it allows executives of construction companies to test if their company is ready for expansion into international markets in general and into a specific country in particular. It is also of relevance to researchers as it demonstrates the successful use of the combined Delphi and AHP methods.     

Expert Systems for Construction Project Monitoring

Potential applications of knowledge based expert systems in the area of construction project monitoring and control are described. Originally developed from research in artificial intelligence, these systems are computer programs that can undertake intelligent tasks currently performed by highly skilled people. While some project monitoring can be accomplished by algorithmic procedures, the capability of knowledge based expert systems to deal with illstructured problems and to be extensively modified over time make them desirable for application in this area. Sample applications and heuristic rules in scheduling and inventory control are provided.     

Integrated Decision Support System for Optimal Renewal Planning of Sewer Networks

Municipalities are under increasing pressure to adopt proactive and optimized renewal strategies to reduce the risks, life-cycle costs, and resources needed to maintain acceptable performance and service levels of their infrastructure assets. A new integrated approach for optimal renewal planning of municipal infrastructure systems has been developed. This paper discusses the application of the proposed approach to implement a GIS-based decision support system (DSS) to support the renewal planning of sewer networks. Condition rating, risk assessment, and prioritization techniques are described. A procedure for identifying and selecting the most suitable renewal technologies is also presented. A genetic algorithm-based multiobjective optimization technique is used to find a Pareto front of feasible solutions, each comprising a set of sewers to be renewed each year, along with the associated costs and expected benefits in terms of condition improvement and risk reduction. The paper also presents an example application of the prototype DSS on the sewer network in Regina, Canada.     

CB-Contract: Case-Based Reasoning Approach to Construction Contract Strategy Formulation

The formulation of an appropriate contract strategy is a fundamental yet critical aspect of contractual arrangement for a project. This paper presents a decision support system (DSS) prototype for contract strategy formulation using the case-based reasoning (CBR) approach. The prototype is called CB-Contract. An overview on the scope and formulation process of contract strategy is provided. Contract strategy is regarded as comprising four main substrategies: (1) work packaging; (2) functional grouping; (3) contract type; and (4) award method. The significance of CBR in contract strategy formulation is examined. The overall architecture of CB-Contract is discussed, with particular emphasis on its knowledge component. A case structure for case representation has been suggested taking into account the important factors that need to be considered while formulating a contract strategy, in particular project characteristics, client’s objectives, and client’s comparative advantages. Issues pertaining to case indexing and similarity calculation for efficient retrieval of similar cases are explored. An illustrative example to obtain similar cases for a given set of project information is presented. Case adaptation that considers the robustness of each substrategy, the compatibility of the substrategies, and the expected effectiveness of the contract strategy is also included in the illustrative example.     

Site Layout Planning using Nonstructural Fuzzy Decision Support System

Site layout planning can affect productivity and is crucial to project success. However, as construction is heterogeneous in the nature of its organizations, project designs, time constraints, environmental effects, etc., site layout planning for each project becomes unique. Affected by many uncertainties (variables) and variations, site layout planning is a typical multiobjective problem. To facilitate the decision-making process for these problems, a nonstructural fuzzy decision support system (NSFDSS) is proposed. NSFDSS integrates both experts’ judgment and computer decision modeling, making it suitable for the appraisal of complicated construction problems. The system allows assessments based on pairwise comparisons of alternatives using semantic operators that can provide a reliable assessment result even under the condition of insufficient precise information.     

Decision Support for Natural Ventilation of Nonresidential Buildings

This paper describes a decision-support framework assisting the design of nonresidential buildings with natural ventilation. The framework is composed of decision modules with input, analysis algorithms and output of natural ventilation design. The framework covers ventilation with natural driving force and mechanical-assisted ventilation. The proposed framework has two major assessment levels: feasibility assessment and comparison of alternative natural ventilation approaches. The feasibility assessment modules assess the potential of the site with the design proposition for natural ventilation in terms of wind, temperature, humidity, noise, and pollution conditions. All of the possible natural ventilation approaches and system designs are assessed by first applying constraint functions to each of the alternatives. Then the comparison of alternative approaches to natural ventilation continues by assessing the critical performance mandates that include energy savings, thermal comfort, acoustic control, indoor air quality, and cost. Approaches are finally ranked based on their performance.