Fuzzy Bi-level Decision-Making Techniques: A Survey

© 2016 the authors. Bi-level decision-making techniques aim to deal with decentralized management problems that feature interactive decision entities distributed throughout a bi-level hierarchy. A challenge in handling bi-level decision problems is that various uncertainties naturally appear in decision-making process. Significant efforts have been devoted that fuzzy set techniques can be used to effectively deal with uncertain issues in bi-level decision-making, known as fuzzy bi-level decision-making techniques, and researchers have successfully gained experience in this area. It is thus vital that an instructive review of current trends in this area should be conducted, not only of the theoretical research but also the practical developments. This paper systematically reviews up-to-date fuzzy bi-level decisionmaking techniques, including models, approaches, algorithms and systems. It also clusters related technique developments into four main categories: basic fuzzy bi-level decision-making, fuzzy bi-level decision-making with multiple optima, fuzzy random bi-level decision-making, and the applications of bi-level decision-making techniques in different domains. By providing state-of-the-art knowledge, this survey paper will directly support researchers and practitioners in their understanding of developments in theoretical research results and applications in relation to fuzzy bi-level decision-making techniques

Tactical project planning under uncertainty: fuzzy approach

At the tactical planning level in a multi-project environment, uncertainties are inherent to the workloads, and costs may be involved for using non-regular capacity and violating project due dates. We propose an approach to identify whether non-regular capacities might be needed to meet the projects' due dates. This problem is known as rough-cut capacity planning (RCCP) problem under uncertainty. We propose a possibilistic approach, which is based on modelling uncertain workloads with fuzzy sets. We present the resulting fuzzy rough-cut capacity planning (FRCCP), and show that we can use the possibilistic approach to provide a robust solution with a fuzzy resource loading profile that supports managers in decision making. We provide a simulated annealing approach to solve the FRCCP, and test it against several existing RCCP approaches. For the experiments we use real life instances from a shipyard maintenance centre

Scheduling optimization of prefabricated construction projects by genetic algorithm

Published: 15 June 2021Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.Linlin Xie, Yajiao Chen and Ruidong Chan

Risk-Based Decision Making Support for Construction Corporate Resource Management

Competitive bidding typically challenges contractors to stay in business by reducing contingency and limiting profit margin, which imposes more prudent resource utilization and allocation decisions during both planning and construction phases of projects. Many of these decisions must be made considering uncertainties that affect resource production and construction performance through several factors such as weather, managerial practices, job-type, and market conditions, etc. Construction decision makers will therefore have varied approaches to deal with these uncertainties based on their risk utility or perception. This research presents the development of a model for investigating the impact of risk-based approaches on construction network outcomes. The current study contributes to development of a model that enables corporate managers to understand the impact of different resource utilization and sharing policies on the overall outcome of their project and to select among optimum planning solutions that satisfy their profit margin and capital limitations. This research also enables corporate decision makers to have more realistic estimates for the profitability of their company, and understand consequences of their decisions in short and long term. Findings of this research provide decision makers with different solutions for profitability of their corporation based on non-dominated optimal time-cost trade-offs, and also broader perspective on how overall time and budget limitations, as well as risk perceptions, can affect the decision-making process. The model is verified and the results are validated through acquiring data from actual large scale construction projects in South Florida

An integrated framework for multi-project planning and control.

The area of project management has been the focus of intensive research for the last three decades. There are a number of studies which have focused on multi-project management, but very few have tackled the need for a tracking system to control and monitor the project in an integrated environment. Some of these studies have covered the multi-project management from the contractor's perspective; or they have tackled one or two of its aspects, such as priority selection, resource allocation, or risk management. The researcher has attempted to show the need for multi-project management systems in which an integrated framework for multi-project planning and control tracking systems (from the owner's perspective rather than the contractors' perspective) is developed; to planning and control under conditions of uncertainty and change. Analytical hierarchy process, mathematical modelling and computer simulation techniques are applied to develop the proposed framework. In multi-project management, each project has its own objective(s) that should be optimised. The analytical hierarchy process is applied to prioritise projects that are received from the applicant accordingly; so that decisions can be made on which project(s) should be launched first. The Mathematical modelling is another method used to solve complex problems, when many projects are running simultaneously. Goal programming is used to minimise the cost and manpower required in a multi-project environment which is usually subject to different constraints. Then simulation is used to manage and control the risk expected in running these projects. In addition, simulation allows project managers to obtain a wide spectrum system on the effects of local changes on the project

Tradition and Innovation in Construction Project Management

This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

Resource assignment in short life technology intensive (SLTI) new product development (NPD)

Enterprises managing multiple concurrent New Product Development (NPD) projects face significant challenges assigning staff to projects in order to achieve launch schedules that maximize financial returns. The challenge is increased with the class of Short Life Technology Intensive (SLTI) products characterized by technical complexity, short development cycles and short revenue life cycles. Technical complexity drives the need to assign staffing resources of various technical disciplines and skill levels. SLTI products are rapidly developed and launched into stationary market windows where the revenue life cycle is short and decreasing with any time-to-market delay. The SLTI-NPD project management decision is to assign staff of varying technical discipline and skill level to minimize the revenue loss due to product launch delays across multiple projects. This dissertation considers an NPD organization responsible for multiple concurrent SLTI projects each characterized by a set of tasks having technical discipline requirements, task duration estimates and logical precedence relationships. Each project has a known potential launch date and potential revenue life cycle. The organization has a group of technical professionals characterized by a range of skill levels in a known set of technical disciplines. The SLTI-NPD resource assignment problem is solved using a multi-step process referred to as the Resource Assignment and Multi-Project Scheduling (RAMPS) decision support tool. Robust scheduling techniques are integrated to develop schedules that consider variation in task and project duration estimates. A valuation function provides a time-value linkage between schedules and the product revenue life cycle for each product. Productivity metrics are developed as the basis for prioritizing projects for resources assignment. The RAMPS tool implements assignment and scheduling algorithms in two phases; (i) a constructive approach that employs priority rule heuristics to derive feasible assignments and schedules and (ii) an improvement heuristic that considers productivity gains that can be achieved by interchanging resources of differing skill levels and corresponding work rates. An experimental analysis is conducted using the RAMPS tool and simulated project and resource data sets. Results show significant productivity and efficiency gains that can be achieved through effective project and resource prioritization and by including consideration of skill level in the assignment of technical resources

Development and implementation of an economic and financial evaluation model of R&D Projects: a case study in the mobility sector

Dissertação de mestrado integrado em Engineering and Industrial ManagementResearch and Development (R&D) projects have limited budgets, depending on the company’s investment and funding capacities available to the company. That being said, the financial dimension should be included in R&D management at every stage to identify possible risks and evaluate the return on investment (ROI), as soon as possible. This research aims to develop a framework to evaluate R&D projects. The developed economic and financial model (FINECON Model) is a decision-making and evaluation tool for R&D projects and their financial scenarios, designed for entrepreneurs, companies with R&D teams, and, lastly, investors or business angels’ usage, allowing the economic and financial viability study of new products, businesses, and technological startups. The proposed methodology was applied to MobiBUS, an intelligent mobility R&D project developed in Bosch Car Multimedia, in collaboration with the University of Minho. The application of the developed model to the case study MobiBUS supported the whole evaluation, the formulation of good and bad hypothetical scenarios, and the delivery of information to the team and potential investors. In conclusion, the MobiBUS project was evaluated as viable, taking into consideration its resources, product, and used technology, as well as sustainable enough to create a start-up. The developed model can be applied to other case studies in mobility contexts or other technological R&D projects.Os projetos de Investigação e Desenvolvimento (I&D) possuem orçamento limitado, e estão dependentes das capacidades de investimento e de financiamento à disposição da empresa. Deste modo, a dimensão financeira deve estar presente na gestão de I&D para que possam ser identificados possíveis riscos e para que seja possível avaliar o retorno do investimento (ROI) o mais precocemente possível. Este projeto de investigação teve como objetivo o desenvolvimento de uma metodologia para avaliar projetos de I&D. O modelo de avaliação económico-financeira desenvolvido (modelo FINECON) é uma ferramenta para a tomada de decisão e avaliação de projetos de I&D e respetivos cenários financeiros, que se destina a empreendedores, empresas com projetos de I&D, ou, em último caso, investidores permitindo analisar as condições de viabilidade económico-financeira de novos produtos, negócios e startups de base tecnológica. A metodologia proposta foi aplicada no MobiBUS, um projeto de mobilidade inteligente de I&D desenvolvido na Bosch Car Multimedia, em colaboração com a Universidade do Minho. A aplicação do modelo ao projeto MobiBUS suportou a sua total avaliação, a formulação hipotética de cenários otimistas e pessimistas, e o fornecimento de informações à equipa e potenciais investidores.Em suma, o projeto MobiBUS avaliou-se viável, tendo em conta os recursos, produto e tecnologia utilizada, e ainda suficientemente sustentável para que se crie uma start-up. O modelo desenvolvido pode ser aplicado noutros casos no contexto particular da mobilidade e noutros projetos de I&D de base tecnológica