Infrastructure Project Selection Research Articles

A Multi-Enterprise Quality Function Deployment Paradigm with Unstructured Decision-Making in Linguistic Contexts

This paper presents an operational framework of unstructured decision-making approach involving quality function deployment (QFD) in an uncertain linguistic context. Firstly, QFD is extended to the multi-enterprise paradigm in a real-world manufacturing environment. Secondly, hesitant fuzzy linguistic term sets (HFLTSs), which facilitate the management and handling of information equivocality, are designed to construct a house of quality (HoQ) in the product planning process. The technique of computing with words is applied to bridge the gap between mechanisms of the human brain and machine processes with fuzzy linguistic term sets. Thirdly, a multi-enterprise QFD pattern is formulated as an unstructured decision-making problem for alternative infrastructure project selection in a manufacturing organization. The inter-relationships of cooperative partners are directly matched with a back propagation neural network (BPNN) to construct the multi-enterprise manufacturing network. The resilience of the manufacturing organization is considered by formulating an outranking method on the basis of HFLTSs to decide on infrastructure project alternatives. Finally, a real-world example, namely, the prototype manufacturing of an automatic transmission for a vehicle, is provided to illustrate the effectiveness of the proposed decision-making approach.

Infrastructure project selection automation using non-structural fuzzy decision support system II

In this study, we develop a web-based Decision-Making Tool (DMT) based on a four-year research project in building the proper multiple criteria Decision-Making Framework (DMF) for infrastructure project selection automation. Several challenges in selecting and prioritizing infrastructure projects include poor front-end planning, lack of project funding, improper investment, unsustainable development, regulatory barriers, and poor coordination among stakeholders. The Non-Structural Fuzzy Decision Support System II (NSFDSS-II) is chosen as the main method applied in the proposed DMF since it could resolve complex multi-criteria problems, even without sufficient information provided. When developing the DMT, Agile software development method is used since the development cycle can be run in a light and fast manner with iterative and incremental processes. The DMT is successfully developed by using PHP, HTML, and JavaScript which implement the proposed NSFDSS-II method. We further tested the decision results from the DMT by using eight real past infrastructure projects from relevant infrastructure agencies in Indonesia, such as the Ministry of Public Works and Housing (MPWH), the Ministry of Transportation, and the Local Government. The DMT outcomes were compared with the actual implementation status and evaluated by an independent expert. It was found that the decision results from the developed DMT are in accordance with the real implementation status of evaluated projects. The DMT is recommended to be used for infrastructure project selection automation. However, despite of its fast and accurate result, the DMT should be tested on larger number of infrastructure projects in the future

Improving the scientific and methodological foundations for determining environmental requirements and criteria for infrastructure projects

The article is devoted to the issue of taking into account the environmental factor in the evaluation and selection of infrastructure projects that are financed with the involvement of funds from the Russian National Wealth Fund. The purpose of the study is to improve the scientific and methodological base for the assessment and selection of infrastructure projects in the face of modern environmental challenges and threats. The work used universal and general scientific methods, methods of empirical and theoretical scientific knowledge, as well as special methods, due to the essence of the object and subject of research. The developed scientific and methodological foundations and proposals for the legal regulation of the assessment and selection of infrastructure projects, taking into account the environmental factor, are presented.

Exploring the Relationship between Project Selection and Approval Criteria and Infrastructure Sustainability

This research aimed at compiling project selection criteria and modelling a robust criterion for infrastructure project selection and approval to enhance sustainability. The decision to select and approve sustainable infrastructure project for development must base on a robust criterion. To handle this properly, first, decision-makers must adopt a robust criterion that aid infrastructure sustainability. The study employed a systematic literature review, methodology and thematic analysis procedure to identify infrastructure project selection and approval criteria from literature. A total of 34 project selection criteria were identified and grouped into five categories. Besides, four approval requirements and four sustainable indicators have been discussed. To avoid any ambiguous and unclear questions in the criterion, 40 professionals were selected purposively for the pilot survey. Descriptive and inferential statistical analyses were employed, and findings were used to improve the criteria. The quantitative phase of the study was conducted on 320 stakeholders who were either project selectors, approvers, advisors, or designers responsible for government projects. S.E.M. were adopted for the analysis and testing of the hypothesis. Moreover, the study has proposed a structure model that integrates identified criteria and indicators to enhance infrastructure selection and approval. Continuous professional development training is vital for all stakeholders to understand and adopt the proposed project selection and approval criteria model to improve infrastructure sustainability performance and to enhance project selection and approval practices. And it was also included in the design brief as a deliverable factor. This outcome serves as preliminary and exploratory research to aid further study on the project selection and approval criteria model for infrastructure sustainability.]

Structure of Infrastructure Project Selection Criteria in Indonesia: A Systematic Approach

Infrastructure project selection is a challenging decision-making problem. While previous literature has pointed out relevant criteria for infrastructure project selection, these criteria need to be contextualized for the effective selection of appropriate projects. This paper aims to identify these criteria in an Indonesian context. A systematic literature review was adopted to identify infrastructure project selection criteria from both local and international practices. It was coupled with twenty semi-structured interviews to draw knowledge and experiences from the Indonesian experts. Finally, a questionnaire survey was distributed and the data was analyzed using factor analysis to obtain the underlying structure of infrastructure project selection criteria. The review of literature outlined 23 selection criteria, out of which 19 criteria were considered important in the Indonesian context. Factor analysis further produced a structure of selection criteria that comprises of five major components: technical criteria, administrative criteria, strategic fit criteria, risks & politics criteria, and innovation. This study contributes by structuring infrastructure project selection criteria that also marks the transitional change from a conventional to a modern decision-making technique as adopted in Indonesia. Thus, it provides a useful reference for decision makers in making a context-based infrastructure project selection.

The Road to Prosperity: A Study on the Efficiency of Resource Allocation in China’s Expressway Construction

This paper presents a new multi-objective mixed integer programming model to prioritize seven highway infrastructure projects. The proposed model explicitly incorporates socio-economics, uncertainty, resource constraints, and interdependencies to deal with the optimal transportation infrastructure project selection problem. Next, project prioritization is determined based on the ANP results, which reflect the interdependency between criteria and a set of feasible candidate projects. Finally, an empirical study of eastwest highway improvement program is conducted to illustrate how the modeling process proceeds. The results show that the proposed model can effectively support a transportation investment policy that best suits the goal of urban land redevelopment for highly urbanized settings. As such, the model can be generalized for other human settlement studies and illustrate the spatially complex characteristics of transportation networks as well as some of the difficulties raised with respect to priority of national capital improvement projects. The research will provide a useful reference for the study of the relationship between highways and regional economic development.

Infrastructure Project Selection & Prioritization: Challenges in the Front-End Planning Phase

Infrastructure Project Selection & Prioritization: Challenges in the Front-End Planning Phase

Expected Characteristics and Features of a Decision-Making Framework for Infrastructure Project Selection: A Structured Thematic Analysis of Interview Data

As the largest economy in Southeast Asia, Indonesia faces various challenges in accelerating infrastructure development. One of these challenges is related to the selection of infrastructure projects that are increasingly stringent considering the continuing growth of infrastructure projects. This paper focuses on issues related to the development of a Decision-Making Framework (DMF) for infrastructure project selection. In order to develop a good DMF, expected characteristics and features must be understood. Thus, this paper aims to identify these expected DMF characteristics and features through a qualitative approach. Twenty semi-structured expert interviews were conducted and analysed based on a structured thematic analysis to identify four key DMF characteristics and three groups of DMF features. These identifications are an important effort in developing a DMF so that it can be fully utilized and well-functioned. Finally, this paper reflects the current expectations in developing a good DMF for infrastructure project selection.

Criteria to consider in selecting and prioritizing infrastructure projects

Infrastructure project selection and prioritization is a challenging decision-making problem. Thus, decision makers are required to develop and use a decision-making framework to evaluate the proposals. The first step in developing such framework is to establish the decision criteria. This research aims to identify these criteria based on a systematic review of literature. A total of 34 decision criteria for infrastructure project selection was identified. In addition, this research has also identified three major facts related to decision criteria and presented a structured model to integrate these decision criteria into a Decision-Making Framework. As a preliminary study, the findings from this research are expected to assist further research on developing a Decision-Making Framework for infrastructure project selection.

Multi-Objective Optimization Models for Improved Decision-Support in Humanitarian Infrastructure Project Selection Problems

The process by which U.S. military organizations select humanitarian infrastructure projects in host countries is hampered by a lack of quantitative decision-support. Addressing this problem is important because the degree of effectiveness of projects selected and completed significantly impacts geo-political implications for the U.S. and, further, directly impacts the quality of life for citizens in host countries. In this paper, a family of multi-objective optimization problems are formulated and solved to explore quantitative, system-level insights on optimal project groupings and comparisons to historical data. Objective functions are found which produce project groupings that match well with historical data, and the optimization model expresses significant information about the sensitivity of solutions in the decision-space. However, imperfection in the matching as well as insights from sensitivities suggests the need for augmentations to improve upon a single organization, optimization-only model. In particular, the use of agent-based modeling is presented for extended work to capture the unmodeled dynamics in the system.

Multicriteria decisions on interdependent infrastructure transportation projects using an evolutionary-based framework

When evaluating transportation infrastructure projects and determining which of them will be carried out from a set of projects and given a budget constraint, several criteria need to be considered in the decision. Standard evaluation practices imply the aggregation of impacts into one utility function which is later optimized. Nevertheless these techniques used for translation of different measuring units into monetary terms are highly controversial. Multicriteria techniques can explicitly deal with different measuring units, however, they are not suitable to model interdependence relationships of projects that share a common characteristic (same route, location or target population, for instance). In this research we model this transportation planning problem, the multi-objective transportation infrastructure project selection problem (MTIPSP), as a constrained multi-objective optimization problem with quadratic objective functions, using a variation of the multi-objective 0–1 knapsack problem plus some additional constraints. Given the combinatorial nature of the problem, an evolutionary-based framework is used for the identification of Pareto solutions, and later, those with non-attractive properties are filtered using a Knee Identification Procedure. The final selection of the projects portfolio is made using a well known multicriteria decision aid method and including the decision makers’ preferences based on the existing context.

Lockheed Martin Space Systems Company Optimizes Infrastructure Project-Portfolio Selection

Lockheed Martin Space Systems Company spends millions of dollars on the maintenance and modernization of its infrastructure each year. Projects often involve investments that cannot be justified purely in terms of net present value or other classical investment-evaluation methods. The options are also restricted because funds that are not spent within a given time frame must be relinquished. Furthermore, some projects may be delayed and the unplanned carryover of their costs moved into the next fiscal year; this causes the postponement or cancellation of other unrelated projects because of in-budget transfers. In this paper, we used multiattribute utility theory and chance-constrained programming to optimize the selection of infrastructure projects. Our solution ensured the selection of high-value projects to maximize the company's performance. These selections were subject to the constraints that a portfolio did not exceed the available budget and that the carryover of the unspent funds to the next fiscal year did not exceed predetermined limits. We used Microsoft Excel to ensure broad accessibility, transparency, user interaction, improved data collection and asset management, and ease-of-use by managers.