An intelligent group decision-support system and its application for project performance evaluation

Purpose: In any organization there are main goals, with lots of projects designed to achieve these goals. It is important for any organization to determine how much these projects affect the achievement of these goals. The purpose of this paper is to develop a fuzzy multiple attribute-based group decision-support system (FMAGDSS) to evaluate projects' performance in promoting the organization's goals utilizing simple additive weighting (SAW) algorithm and technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. The proposed FMAGDSS deals with choosing the most appropriate fuzzy ranking algorithm for solving a given fuzzy multi attribute decision making (FMADM) problem with both qualitative and quantitative criteria (attributes), and uncertain judgments of decision makers. Design/methodology/approach: In this paper, a FMAGDSS model is designed to determine scores and ranks of every project in promoting the organization's goals. In the first step of FMAGDSS model, all projects are assessed by experts based on evaluation criteria and the organization's goals. The proposed FMAGDSS model will then choose the most appropriate fuzzy ranking method to solve the given FMADM problem. Finally, a sensitivity analysis system is developed to assess the reliability of the decision-making process and provide an opportunity to analyze the impacts of "criteria weights" and "projects" performance' on evaluating projects in achieving the organizations' goals, and to assess the reliability of the decision-making process. In addition, a software prototype has been developed on the basis of FMAGDSS model that can be applied to solve every FMADM problem that needs to rank alternatives according to certain attributes. Findings: The result of this study simplifies and accelerates the evaluation process. The proposed system not only helps organizations to choose the most efficient projects for sustainable development, but also helps them to assess the reliability of the decision-making process, and decrease the uncertainty in final decision caused by uncertain judgment of decision makers. Research limitations/implications: Future studies are suggested to expand this system to evaluate and rank the project proposals. To achieve this goal, the efficiency of the projects in line with organization's goals, should be predicted.Originality/value: This study contributes to the relevant literature by proposing a FMAGDSS model to evaluate projects in promoting organization's goals. The proposed FMAGDSS has ability to choose the most appropriate fuzzy ranking algorithm to solve a given FMADM problem based on the type and the number of attributes and alternatives, considering the least computation and time consumption for ranking alternatives. © Emerald Group Publishing Limited

The project portfolio selection and scheduling problem: mathematical model and algorithms

This paper investigates the problem of selecting and scheduling a set of projects among available projects. Each project consists of several tasks and to perform each one some resource is required. The objective is to maximize total benefit. The paper constructs a mathematical formulation in form of mixed integer linear programming model. Three effective metaheuristics in form of the imperialist competitive algorithm, simulated annealing and genetic algorithm are developed to solve such a hard problem. The proposed algorithms employ advanced operators. The performance of the proposed algorithms is numerically evaluated. The results show the high performance of the imperialist competitive algorithm outperforms the other algorithms

AN EXCEL-BASED DECISION SUPPORT SYSTEM FOR SCORING AND RANKING PROPOSED R&D PROJECTS

One of the most challenging aspects of technology management is the selection of research and development (R&D) projects from among a group of proposals. This paper introduces an interactive, user-friendly decision support system for evaluating and ranking R&D projects and demonstrates its application on an example R&D program. It employs the scoring methodology developed by Henriksen and Traynor to provide a practical technique that considers both project merit and project cost in the evaluation process, while explicitly accounting for trade-offs among multiple decision criteria.1 The framework of the Excel-based system, PScore, is presented with an emphasis on the potential benefits of using this methodology with computer-automated extensions that facilitate and enhance managerial review and decision-making capabilities.R&D project evaluation, R&D project selection, scoring, ranking, interactive decision support

Eco-design implementation for complex industrial system (From scenario-based LCA to the definition of an eco-innovative R&D projects portfolio)

Face à l émergence des problématiques environnementales issues des activités humaines, l écoconception s attache à offrir une réponse satisfaisante dans le domaine de la conception de produits et services. Cependant, lorsque les produits considérés deviennent des systèmes industriels complexes, caractérisés entre autres par un grand nombre de composants et sous-systèmes, un cycle de vie extrêmement long et incertain, ou des interactions complexes avec leur environnement géographique et industriel, un manque évident de méthodologies et d outils se fait ressentir. Ce changement d échelle apporte en effet des contraintes différentes aussi bien dans l évaluation des impacts environnementaux générés au cours du cycle de vie du système (gestion et qualité des données, niveau de détail de l étude par rapport aux ressources disponibles ) que dans l identification de réponses adaptées (gestion de la multidisciplinarité et des ressources disponibles, formation des acteurs, inclusion dans un contexte de R&D très amont ). Cette thèse vise donc à développer une méthodologie de mise en œuvre d une démarche d éco-conception de systèmes industriels complexes. Une méthodologie générale est tout d abord proposée, basée sur un processus DMAIC (Define, Measure, Analyse, Improve, Control). Cette méthodologie permet de définir de manière formalisée le cadre de la démarche (objectifs, ressources, périmètre, phasage ) et d accompagner rigoureusement l approche d écoconception sur le système considéré. Une première étape d évaluation environnementale basée sur l Analyse du Cycle de Vie (ACV) à haut niveau systémique est ainsi réalisée. Etant donnée la complexité du cycle de vie considéré et la variabilité d exploitation d un système industriel d un site à l autre, une approche par scénario est proposée afin d appréhender rapidement l étendue possible des impacts environnementaux. Les scénarios d exploitation sont définis à l aide de la matrice SRI (Stranford Research Institute) et intègrent de nombreux éléments rarement abordés en ACV, comme la maintenance préventive et corrective, la mise à niveau des sous-systèmes ou encore la modulation de la durée de vie du système en fonction du contexte économique. A l issue de cette ACV les principaux postes impactants du cycle de vie du système sont connus et permettent d entreprendre la seconde partie de la démarche d éco-conception centrée sur l amélioration environnementale. Un groupe de travail multidisciplinaire est réuni lors d une séance de créativité centrée autour de la roue de la stratégie d éco-conception (ou roue de Brezet), un outil d éco-innovation peu consommateur de ressources et ne nécessitant qu une faible expertise environnementale. Les idées générées en créativité sont alors traitées par trois filtres successifs, qui permettent : (1) de présélectionner les meilleurs projets et de les approfondir ; (2) de constituer un portefeuille de projets de R&D par une approche multicritère évaluant leur performance environnementale, mais également technique, économique et de création de valeurs pour les clients ; (3) de contrôler l équilibre du portefeuille constitué en fonction de la stratégie de l entreprise et de la diversité des projets considérés (aspects court/moyen/long terme, niveau systémique considéré ). L ensemble des travaux a été appliqué et validé chez Alstom Grid sur des sous-stations de conversion électrique utilisées dans l industrie de l aluminium primaire. Le déploiement de la méthodologie a permis d initier une démarche solide d écoconception reconnue par l entreprise et de générer au final un portefeuille de 9 projets de R&D écoinnovants qui seront mis en œuvre dans les prochains mois.Face to the growing awareness of environmental concerns issued from human activities, eco-design aims at offering a satisfying answer in the products and services development field. However when the considered products become complex industrial systems, there is a lack of adapted methodologies and tools. These systems are among others characterised by a large number of components and subsystems, an extremely long and uncertain life cycle, or complex interactions with their geographical and industrial environment. This change of scale actually brings different constraints, as well in the evaluation of environmental impacts generated all along the system life cycle (data management and quality, detail level according to available resources ) as in the identification of adapted answers (management of multidisciplinary aspects and available resources, players training, inclusion in an upstream R&D context ). So this dissertation aims at developing a methodology to implement ecodesign of complex industrial systems. A general methodology is first proposed, based on a DMAIC process (Define, Measure, Analyse, Improve, Control). This methodology allows defining in a structured way the framework (objectives, resources, perimeter, phasing ) and rigorously supporting the ecodesign approach applied on the system. A first step of environmental evaluation based on Life-Cycle Assessment (LCA) is thus performed at a high systemic level. Given the complexity of the system life cycle as well as the exploitation variability that may exist from one site to another, a scenario-based approach is proposed to quickly consider the space of possible environmental impacts. Scenarios of exploitation are defined thanks to the SRI (Stanford Research Institute) matrix and they include numerous elements that are rarely considered in LCA, like preventive and corrective maintenance, subsystems upgrading or lifetime modulation according to the economic context. At the conclusion of this LCA the main impacting elements of the system life cycle are known and they permit to initiate the second step of the eco-design approach centred on environmental improvement. A multidisciplinary working group perform a creativity session centred on the eco-design strategy wheel (or Brezet wheel), a resource-efficient eco-innovation tool that requires only a basic environmental knowledge. Ideas generated during creativity are then analysed through three successive filters allowing: (1) to pre-select and to refine the best projects; (2) to build a R&D projects portfolio thanks to a multi-criteria approach assessing not only their environmental performance, but also their technical, economic and customers value creation performance; (3) to control the portfolio balance according to the company strategy and the projects diversity (short/middle/long term aspect, systemic level ). All this work was applied and validated at Alstom Grid on electrical conversion substations used in the primary aluminium industry. The methodology deployment has allowed initiating a robust eco-design approach recognized by the company and finally generating a portfolio composed of 9 eco-innovative R&D projects that will be started in the coming months.CHATENAY MALABRY-Ecole centrale (920192301) / SudocSudocFranceF

An analysis of reasonableness models for research assessments

Individuals who screen research grant applications often select candidates on the basis of a few key parameters; success or failure can be reduced to a series of peer-reviewed Likert scores on as little as four criteria: risk, relevance, return, and reasonableness. Despite the vital impact these assessments have upon the sponsors, researchers, and society in general as a benefactor of the research, there is little empirical research into the peer-review process. The purpose of this study was to investigate how reviewers evaluate reasonableness and how the process can be modeled in a decision support system. The research questions both address the relationship between an individual\u27s estimates of reasonableness and the indicators of scope, resources, cost, and schedule as well as evaluate the performance of several cognitive models as predictors of reasonableness. Building upon Brunswik\u27s theory of probabilistic functionalism, a survey methodology was used to implement a policy-capturing exercise that yielded a quantitative baseline of reasonableness estimates. The subsequent data analysis addressed the predictive performance of six cognitive models as measured by the mean-square-deviation between the models and the data. A novel mapping approach developed by von Helversen and Rieskamp, a fuzzy logic model, and an exemplar model were found to outperform classic linear regression. A neural network model and the QuickEst heuristic model did not perform as well as linear regression. This information can be used in a decision support system to improve the reliability and validity of future research assessments. The positive social impact of this work would be more efficient allocation and prioritization of increasingly scarce research funds in areas of science such as social, psychological, medical, pharmaceutical, and engineering