Franck Taillandier

Evolutive Risk Breakdown Structure for managing construction project risks: application to a railway project in Algeria

Construction projects are subject to numerous risks that could have consequences on project success. Therefore, it is necessary to manage project risks by modelling them. Risk Breakdown Structure (RBS) is a hierarchical formalisation method of risks facilitating their identification and analysis. Project risks have a dynamic nature; they evolve throughout the project. Consequently, RBS needs to be adapted continuously throughout the project. This paper proposes an evolutionary vision of RBS, which allows simultaneous consideration of risk variations and their impact on RBS structure. The method is applied retrospectively to a railway infrastructure project in Algeria, in order to illustrate the principle of the process and to highlight its interest.

An interactive decision support method for real estate management in a multi-criteria framework – REMIND

Managing a housing stock involves complex decision making such as the design of a multiyear action plan pertaining to the maintenance and upgrading of the properties. In order to address this problem, we developed a novel interactive decision support method (REMIND) to assist a housing stock manager in the progressive design and choice of a multiyear action plan based on multiple criteria. It uses a filtering approach both at the individual action level and at the global scenario level where the housing stock manager can gradually express preferences and conduct what-if analyses. An optimization component based on Tabu search allows the decision-maker to obtain a set of good plans from which he can choose the one to implement. The quality of a plan is defined in terms of how well it meets the goals on each criterion. The application of the method was tested in a leading French property management company.

Decision aiding for lower soil risk in urban planning operation

ABSTRACT Urban development projects carry major issues and are also subject to significant risks. Soil (surface and underground) can be the source of uncertainties that may induce risks. Soil risks are often reduced by experts to geotechnical issues. The SORIA method (SOil RIsk Analysis for urban planning project) was developed into the ANR-D2SOU project to integrate a more comprehensive analysis related to soil/subsoil since the early stages of the project. More specifically, SORIA is a risk analysis method, considering soil/subsoil evaluation methods to optimise the project from this perspective. For this purpose, SORIA uses a utility-based approach coupled with a risk knowledge base. This method has been experimented on a real case, which is presented in this paper.

A multicriteria evaluation of real estate properties based on environmental impacts

This paper presents an evaluation method of the state of real estate properties as a first step towards the elaboration of action plans for improving the environmental characteristics of a building stock. This multicriteria and multilevel evaluation method takes into account both the decision maker and the building specialists’ point of views. One of the main challenges is in the translation of data obtained from tools such as life cycle analysis, thermal simulation or global cost analysis into high level information meaningful to the decision maker. This paper focuses on the transition mechanisms of the evaluations between the two types of actors. The proposed method is based on the comparisons of data with reference values and on multicriteria aggregation using ELECTRE TRI. We illustrate the working of the proposed method on a building stock example.

A decision support tool approach based on the Electre TRI-B method for the valorisation of tropical timbers from the Congo Basin: an application for glulam products

An alternative approach to the formal management strategy of tropical timber species from the Congo Basin was investigated. It focused on the development of glulam, with an aim to specify a decision support model for the valorisation of tropical timber species considered for use in these products. There were 76 forest species analysed regarding ecological, engineering and social criteria according to their major uses. The Electre TRI-B multicriteria sorting method was used. The main result was a new and robust classification tool of timber species from the Congo Basin, corresponding to their multicriteria consensus degree. The potentials of the new grouping system were analysed. Species that meet a great majority of criteria were identified. They were highly suitable for sustaining the market position of glulam products. Implementing this strategy may significantly improve the management and increase the value of the timber species from the Congo Basin, while preserving endangered species.

A new agent-based model to manage construction project risks – application to the crossroad of Bab El Karmadine at Tlemcen

Risk management in a construction project is a key but extremely complex issue. To answer it, we developed Stochastic Multi-agent simulAtion for Construction projeCt (SMACC), a simulation tool for construction project that considers risks. SMACC proposes, using an agent-based model with a stochastic approach, to assess risk consequences for each project stakeholder. This dynamic model enables to build indicators, which can be used as criteria in a decision support process. A former version of SMACC had some flaws such as a too quantitative approach, a poor modelling of resources or a high rigidity of the process description. Furthermore, formally and conceptually, the SMACC model had a weak structuration of knowledge. An improved version based on an ontology has been developed, called SMACC2. The paper presents this new version as well as a real case of application: the building of the crossroad of Bab El Karmadine at Tlemcen.

Risk Management in Construction Project Using Agent-Based Simulation

In recent years, intensive research and development have been done in the area of construction project risk management. Indeed, an efficient risk management is mandatory to project success. However, implementing such a management is complex because of the diversity and the dynamic nature of the risk. Moreover, each of the project stakeholders has his/her own risks, his/her own vision and his/her own action on the project and on risks. In this paper, we propose an agent-based model called SMACC to assess the impact of risks on the project. This model allows to test different risk mitigation strategies to measure their impact on the project. An application on a real project is also proposed to demonstrate the operability and the value of the proposed approach.