Multiobjective Optimization for Maintenance Decision Making in Infrastructure Asset Management

Abstract

Maintenance decision making that selects appropriate maintenance strategies for a road network is an important and complex part of infrastructure asset management (IAM). Multiobjective optimization (MOO) can help in simplifying a decision making problem with multiple objectives and trading off objectives by identifying efficient solutions. Therefore, MOO is a helpful tool in the decision-making process. The main objective of this study is to analyze the optimization problem involved in practical decision-making processes using MOO and to identify efficient solutions in the context of maintenance decision making. To accomplish this aim, this paper (1) introduces decision making in IAM along with a discussion of previous applications of optimization; (2) discusses the mathematical formulation of optimization problems in the context of IAM decision making; (3) proposes an optimization method known as dichotomic approach (DA) to solve the optimization problems of decision making by identifying efficient solutions; (4) compares DA with the nondominated sorting genetic algorithm II (NSGA II) using a practical maintenance decision making case study; and (5) discusses other issues related with the DA solution process, such as controlling the number of identified solutions, identification of nonsupported solutions, and decision making with three or more objectives. This paper explains MOO and efficient solutions in maintenance decision-making process in IAM; and introduces a MOO technique, DA, to solve optimization problems associated with maintenance decision making. When compared to NSGA II, DA proves to be more effective in terms of solution quality, computation time, and implementation.