Multi-criteria optimization - Application in the construction industry
Article REF: S7214 V1

Multi-criteria optimization - Application in the construction industry

Authors : Igal M. SHOHET, Eldad PERELSTEIN

Publication date: June 10, 2001 | Lire en français

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AUTHORS

  • Igal M. SHOHET

  • Eldad PERELSTEIN: Faculty of Civil Engineering - Technion, Israel Institute of Technology

 INTRODUCTION

Translation from English by Anne-Marie GAULIER

One of the major problems facing institutional organizations with a large number of buildings is the constraint of a limited budget for maintenance and rehabilitation. They face the dilemma of allocating limited financial resources to different projects. This problem can be formulated as follows:

  • Among a large number of potential rehabilitation projects: which to choose?

  • what is the "optimal" level of intervention in each project that would maximize total profit (in terms of cost, lifetime, level of performance and logistics)?

The problem was broken down into two phases:

  • develop a methodology to determine the cost/benefit ratios of several different intervention modes in each project considered separately (intra-project study);

  • develop an optimization algorithm to determine priorities for resource allocation among different projects, with an objective function that will lead to maximized total profits (inter-project study).

The model proposed for the solution of this problem comprises four levels:

(1) Systematic assessment of plant condition (physical and functional suitability);

(2) generation of alternative rehabilitation or upgrading solutions based on the results of the condition assessment;

(3) Drawing up cost/profit tables for each project, highlighting the different levels of intervention, their costs and the corresponding profits;

(4) allocation of financial resources between the most interesting alternatives, i.e. those that guarantee maximization of total profit for a given total budget. The proposed search mechanism uses dynamic programming to determine configurations close to the optimum.

We conclude the article with a representative example that describes the 4-phase module and the composite criteria for determining priorities.

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