Bruno Urli

Project Management in North America, Stability of the Concepts

The field of project management has undergone very important developments during the last 10 years, if one considers the very large amount of activities that it has generated and continues to generate (papers in journals, dedicated journals, books, meetings, applications, etc.). Even if project management has reached some maturity—due to the construction of a common referential, a common body of knowledge called A Guide to the Project Management Body of Knowledge (PMBOK® Guide)—its future is subject to questions and debate among its researchers. What is the evolution of the field? What is its structure? Is it integrating new topics that correspond to management by project? In order to answer such questions at least partially, we have studied project management literature by the method of associated words (scientometric analysis) and the software, “Leximappe.” All the papers that are relative to project management and included in the bibliographic ABI-INFORM database from 1987 to 1996 have been analyzed. In this paper, we present the main results of this study.

PROMISE/scenarios: An interactive method for multiobjective stochastic linear programming under partial uncertainty

Abstract In many real contexts where the multiobjective stochastic linear programming can be used as a modelling approach, the decision maker is in general placed in a situation of incomplete information concerning the uncertain parameters of the problem. A good way to express that incomplete information consists in resorting to the idea of scenarios relatively to the objectives and constraints of the stochastic program. While the authors who have suggested methods based on scenarios suppose that the probabilities of those scenarios are known, in this paper we propose a scenarios approach where the probabilities of scenarios is only incompletely specified according to a ranking. That interactive method, called PROMISE/scenarios, is presented and is illustrated by a didactic example.

An Interactive Method To Multiobjective Linear Programming Problems With Interval Coefficients

AbstractIn the context of multiobjective linear programming (MOLP) problems where there is indetermination around some parameters, we suppose that the decision maker knows only the limits of variation of these parameters and eventually one of their central values. For such situations, we have proposed (cf. Urli and Nadeau, 1990) a general methodology wich enables us to transform the non deterministic MOLP problem into a deterministic one and after to solve the latter program by an interactive approach derived from the STEM method. In the present paper we develop a particular method based on that general methodology and we illustrate it by a didactic example.

Multiobjective Stochastic Linear Programming with Incomplete Information: A General Methodology

Numerous multiobjective linear programming methods have been proposed in the last two decades for contexts where the parameters are deterministic. In many real situations, however, parameters of a stochastic nature arise and the analyst is, as a result, confronted with a stochastic multiobjective linear programming problem. Recently, some methods have been developed to deal with this kind of problems; in most of them, the decision maker is supposed to be placed in a risky situation, i.e. a situation where he can associate probability distributions to the stochastic parameters. In many cases, we believe that it would be more realistic to suppose that the decision maker is in a situation of partial uncertainty, i.e. a situation where he possesses only an incomplete information about the stochastic parameters; for example, he could be able to precise only the bounds of variation of the parameters and eventually, their central values. For such situations, we propose a general multiobjective stochastic linear programming methodology which includes many modes of transformation of the stochastic objectives and constraints in order to obtain an equivalent multiobjective deterministic linear programming problem. Finally, this deterministic equivalent program is solved by an interactive method derived from STEM. Our methodology will be illustrated through a didactical example.

Project portfolio selection model, a realistic approach

Today, more and more companies are moving towards a project-oriented way of managing their businesses. It sets certain challenges to companies. How to make sure that the selected projects are implementing the strategy of the company? Are the scarce resources (financial, human capital) allocated to the right projects? Which projects to select, which projects to pursue and which to kill? Project portfolio management tackles these problems and has become an important topic in recent years. Nevertheless, different empirical studies highlighted the fact that these models are not used in practice. We propose an approach based on the generation of efficient portfolios by the metaheuristic SSPMO1 and on an “objective” analysis of these portfolios in order to make good recommendation to the portfolio committee or the decision makers.

Design System Assessment Tool

In 2010, an exploratory survey focused on design methods, tools and techniques, was conducted in order to understand what type of design practices are used in Small and Medium-sized Enterprises (SMES) located in Eastern Quebec. This study reveals that most SMEs declared using a structured design process while very few are regular users of structured Methods, sophisticated Tools, or specialized design Techniques (MTT). Because the results suggest that the design process in SMEs is not as structured as could be expected a new research was launched. Specifically, the research objective consist to identify the most important determinants of design performance and to develop indicators for assessing the design process as well as the other dimensions of design projects. In this model, six dimensions describe what is called the design system: the environmental dimension, the human and techno-scientific axis, management, the design process and the product aspects. The Dimensions are evaluated using an assortment of variables (descriptors) to assess the “design system” of an organization. Each descriptor is related to the following issues: (i) the type of methods, tools and activities used by the organization, (ii) the importance of the descriptor according to the project success, (iii) the performance level of the organization in that matter and (iv) the involvement of the partners. The questionnaire has been tested and refined on a pilot basis by eight partners. In addition to the model and the questionnaire, the paper presents an overview of the survey results and it illustrates how the assessment tool can be used to identify the challenges that a company must face in order to improve its design practices. Finally, it exposes the strengths and weaknesses of the questionnaire and it identifies the improvements to be made before to use it as base of an observatory intended to measure and monitor the evolution of design practices of organizations.

PROMISE: A DSS for multiple objective stochastic linear programming problems

Most of the multiple objective linear programming (MOLP) methods which have been proposed in the last fifteen years suppose deterministic contexts, but because many real problems imply uncertainty, some methods have been recently developed to deal with MOLP problems in stochastic contexts. In order to help the decision maker (DM) who is placed before such stochastic MOLP problems, we have built a Decision Support System called PROMISE. On the one hand, our DSS enables the DM to identify many current stochastic contexts: risky situations and also situations of partial uncertainty. On the other hand, according to the nature of the uncertainty, our DSS enables the DM to choose the most appropriate interactive stochastic MOLP method among the available methods, if such a method exists, and to solve his problem via the chosen method.