Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

A review of application of multi-criteria decision making methods in construction

Construction is an area of study wherein making decisions adequately can mean the difference between success and failure. Moreover, most of the activities belonging to this sector involve taking into account a large number of conflicting aspects, which hinders their management as a whole. Multi-criteria decision making analysis arose to model complex problems like these. This paper reviews the application of 22 different methods belonging to this discipline in various areas of the construction industry clustered in 11 categories. The most significant methods are briefly discussed, pointing out their principal strengths and limitations. Furthermore, the data gathered while performing the paper are statistically analysed to identify different trends concerning the use of these techniques. The review shows their usefulness in characterizing very different decision making environments, highlighting the reliability acquired by the most pragmatic and widespread methods and the emergent tendency to use some of them in combination

A. I. Utilization in the Construction Business: A review on present state and potential for Elenia Oy

The thesis examines the present applications of artificial intelligence in the construction busi-ness domain. Nowadays, businesses are focusing on the safety of an operating environment. In a project-based business, managing projects and portfolios with safety management is significantly important. Lack of knowledge is rarely a root cause of undesired deviations. More often, the deviations in processes are related to an irregularity in compliance with the instructions and rules. With the assistance of AI-based tools, such as machine learning, one can improve efficiency on safety and project management tasks. The thesis provides a gen-eral view of artificial intelligence and a review of present approaches on AI utilization in the construction domain. Also, the thesis suggests the next steps for the utilization of AI in Elenia’s construction business. The first section of the thesis gives an overall view of artificial intelligence. In the second and third sections, a review of the present utilization approaches is examined. In the second section, the utilization is examined in the construction site safety domain. In the third section the examined field is related to the project management do-main. The most common way to utilize AI were to exploit existing data for risk prediction and relationship detection. The risks differ from the examined domain. Thus, building a machine learning model is use-case related. There are various ways to utilize different models to achieve the benefits of machine learning. In Elenia Oy’s activities managing projects have a key role for achieving company’s mission: Electrifying life. The electric grids demand continu-ous maintenance and consistent development. One part of the development is replacement of components that have reached end of the technical lifecycle. For example, replacement can be executed in Elenia’s Säävarma projects. The development of occupational safety Elenia together with its partners has committed for safety manifesto. The key theme of safe-ty manifesto is to render everyone related to Elenia’s work field to return home in good health. The key approach of thesis was to find widely different approaches to utilize an AI for the development of safety and project objectives.Tässä diplomityössä selvitettiin rakentamisliiketoimintoihin liittyviä tekoälyn käyttökohteita. Nykyisin liiketoiminnoissa keskitytään operatiivisten toimintojen turvallisuuteen. Projektiliike-toiminnassa projektien ja portfolioiden johtaminen yhdessä turvallisuusjohtamisen kanssa on huomattavan tärkeää. Tiedon puute on harvoin juurisyy ei-toivotuille poikkeamille. Useammin poikkeamat prosesseissa johtuvat epäsäännöllisyydestä ohjeistuksien ja sääntöjen noudatta-misen suhteen. Tekoälyyn pohjautuvien työkalujen, kuten koneoppiminen, avulla on mahdol-lista kehittää turvallisuuteen ja projektijohtamiseen liittyvien tehtävien tehokkuutta. Tutkielma sisältää yleisen katsauksen tekoälyyn ja tarkastelun nykyisistä lähestymistavoista tekoälyn hyödyntämiseen rakentamisliiketoimintoihin liittyen. Lisäksi työssä muodostetaan ehdotukset tuleville vaiheille tekoälyn hyödyntämiseen Elenian rakentamisliiketoiminnassa. Ensimmäisessä osassa käydään läpi yleiskatsaus tekoälyyn liittyen. Toisessa ja kolmannessa osassa työtä tar-kastellaan nykyisiä tekoälyn käyttökohteita. Toisessa osassa tarkastellaan rakentamistöiden turvallisuuteen liittyviä hyödyntämiskohteita. Kolmannessa osassa vastaava tarkastelu keskit-tyy projekti ja portfoliojohtamisen toimintaympäristöön. Yleisin tapa hyödyntää tekoälyä on selvittää ja tunnistaa toimintaympäristön riskeihin liittyvien tekijöiden suhteita toisiinsa. Erilai-sissa toimintaympäristöissä on erilaisia riskejä, joiden esiintymisen todennäköisyyttä on syytä pienentää. Koneoppimismallien rakentamisen toteutus on käyttökohde sidonnainen, joten on monia tapoja hyödyntää koneoppimista. Elenia Oy:n toiminnassa projektit ja niiden hallinta ovat keskeisessä osassa mahdollistamassa yhtiön missiota: Elämää sähköistämässä. Sähköver-kot vaativat jatkuvaa kunnossapitoa ja johdonmukaista kehittämistä. Osa tätä kehittämistä on teknisen käyttöiän saavuttaneiden komponenttien uusinta, esimerkiksi Elenian Säävarma-hankkeissa. Työturvallisuuden edistämiseksi Elenia on yhdessä kumppaniensa kanssa allekir-joittanut Turvallisuusmanifestin, jonka keskeinen teema on mahdollistaa kaikkien Elenian töissä olevien henkilöiden turvallisen palaamisen terveenä kotiin. Tutkielman keskeisenä lähestymis-tapana oli etsiä laajasti erilaisia tapoja hyödyntää tekoälyä liittyen turvallisuus- ja projektita-voitteiden kehittämiseen

Multi-criterion two-sided matching of Public-Private Partnership infrastructure projects: Criteria and methods

Two kinds of evaluative criteria are associated with Public-Private Partnership (PPP) infrastructure projects, i.e., private evaluative criteria and public evaluative criteria. These evaluative criteria are inversely related, that is, the higher the public benefits; the lower the private surplus. To balance evaluative criteria in the Two-Sided Matching (TSM) decision, this paper develops a quantitative matching decision model to select an optimal matching scheme for PPP infrastructure projects based on the Hesitant Fuzzy Set (HFS) under unknown evaluative criterion weights. In the model, HFS is introduced to describe values of the evaluative criteria and multi-criterion information is fully considered given by groups. The optimal model is built and solved by maximizing the whole deviation of each criterion so that the evaluative criterion weights are determined objectively. Then, the match-degree of the two sides is calculated and a multi-objective optimization model is introduced to select an optimal matching scheme v ia a min-max approach. The results provide new insights and implications of the influence on evaluative criteria in the TSM decision

The role of similarity measurement in an agent-based supplier selection framework

Similarity measurement is a critical component in any case-based reasoning (CBR) system. CBR is a superior technique for solving new problems based on previous experiences. Main assumption in CBR relies on the hypothesis that states similar problems should have similar solutions. This paper describes a comparative analysis on several commonly used similarity measures (Canberra, Clark, and Normalized Euclidean distance) in retrieving phase of the case-based reasoning approach to facilitate supplier selection. In addition, the proposed agent-based supplier selection framework was designed to use customer’s defined weights to evaluate the price, volume, quality grade, and delivery date of supply materials, and also provide them with alternative products which are closest to their first order if it was out of stock. Finally, based on the proposed framework, a numerical example of the used approach is illustrated

Risk management strategy of construction projects in China

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyEmbarking on a construction project means taking a risk. Project risk management (PRM) provides an effective approach to improve decision making and minimise project risk. Project risks may not possess the same level of significance for different countries, markets and projects. Current research on PRM in China has been rather theoretical, addressing technology issues. Considering the current practice in the Chinese construction industry (CCl), the PRM needs understanding and support from the industry and a mature market environment. This research aims to establish PRM strategies for identifying and adopting the best practice to provide practical guidelines for the CCl, thus improving the PRM, motivating the reform of the Chinese construction market, and enabling the CCl to function in the competitive environment of globalisation. An extensive literature review and a number of case studies for construction projects in China have been conducted, addressing issues closely related to the research. A systematic analysis is employed and developed for project planning and decision making. Contractual risks are considered as the first step and catalyst for improving the PRM in the CCl. Built on the findings from the case studies and analysis, the research puts forward a framework of contractual risk management to study the concept, identification and classification of contractual risks. Contract interfaces are analysed for contractual risk management under various project procurement routes (PPRs). The potentially large improvements to the PRM and reform of the Chinese construction market from the introduction and application of innovative PPRs and their contractual conditions are addressed. Two mathematical models -a probabilistic analysis model and an effective information entropy model for key contractual risks -are presented. The validity and applicability of the models are demonstrated with sample data for the CCl. Detailed recommendations and guidelines for the implementation of the proposed strategies are suggested

Suppliers Selection In Manufacturing Industries And Associated Multi-Objective Desicion Making Methods: Past, Present And The Future

Nowadays, many manufacturing companies have decided to use other companies’ competencies and outsource part of their manufacturing processes and business to suppliers globally in order to reduce costs, improve quality of products, explore or expand new markets, and offer better services to customers, etc. The decisions have rendered manufacturing organizations with new challenges. Organizations need to evaluate their suppliers' performance, and take account of their weakness and strength in order to win and survive in highly competitive global marketplaces. Hence, suppliers evaluation and selection are taken as an important strategy for manufactring enterprises. This paper aims to provide a comprehensive and critical review on suppliers selection and the formulation of different criteria for suppliers selection, the associated multi-objctive decision makings, selecion algorithms, and their implementation and application perspectives. Furthermore, individual and integrated suppliers selection approaches are presented, including Analytic hierarchy process (AHP), Analytic network process (ANP), and Mathematical programming (MP). Linear programming (LP), Integer programming (IP), Data envelopment analysis (DEA) and Goal programming (GP) are discussed with in-depth. The paper concludes with further discussion on the potential and application of suppliers selection approach for the broad manufacturing industry

Delivering services by building and running virtual organisations

Non peer reviewedPostprin