Multi-objective Billiards-Inspired Optimization Algorithm for Construction Management Problems
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RESEARCH PAPER
Multi‑objective Billiards‑Inspired Optimization Algorithm for Construction Management Problems M. Rastegar Moghaddam1 · M. Khanzadi1 · A. Kaveh1 Received: 20 June 2020 / Accepted: 9 September 2020 © Shiraz University 2020
Abstract This paper introduces an efficient multi-objective algorithm for handling multi-objective problems. The main genesis of this metaheuristic is the game of billiards and the physical background of the collision between balls, which govern its process. Due to reinforcing this algorithm for handling multi-objective problems, an external repository for storing non-dominated solutions, the maximin strategy for grouping balls, and a roulette-wheel selection mechanism for choosing pockets from the repository are employed. The proposed multi-objective billiards-inspired optimization algorithm (MOBOA) performance is verified using ten unconstrained multi-objective mathematical benchmark functions, including bi-objective and tri-objective cases with different characteristics. The application of this algorithm is examined in three constrained construction project management problems management including construction site layout planning, building materials design, and project scheduling. The results show that MOBOA is able to provide competitive trade-off solutions with acceptable convergence and uniform diversity. Keywords Multi-objective optimization · Metaheuristic · Multi-objective billiards-inspired optimization algorithm · Construction project management
1 Introduction The mission of the construction sector is to provide buildings and infrastructures to meet people’s needs (Ilbeigi and Ebrahimi Meimand 2020). In this way, practitioners, besides design and execution issues, face some challenges comprising, budget limitations, contractual scheduling constraints, quality requirements, safety and environmental concerns, convenient material logistic, sustainability rating system requirements, stakeholder dissatisfaction with project delays, etc. (Alothaimeen and Arditi 2019). Under such circumstances, to handle all aspects, it is necessary to consider construction project problems as a multi-objective optimization problem (MOP). The process of optimizing several conflicting objectives simultaneously is named multi-objective optimization. The prominent characteristic of this category of optimization problems is that no singular solution exists,
* A. Kaveh [email protected] 1
School of Civil Engineering, Iran University of Science and Technology, Narmak, Tehran 16846‑13114, Iran
but a set of solutions that delivers a trade-off among objectives is available (Branke et al. 2008). According to the role of decision-makers, two main approaches are common in this class of optimization, priori and posteriori preferences. The priori methods are techniques where the decision-makers articulate preferences before optimization, like the weighted-sum, the 𝜀-constraint methods, and goal programming. The weighted-sum method combines a set of objectives into a single objective by premultip
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