Automated multi-objective optimization system for airport site layouts

Khalafallah, Ahmed; El‐Rayes, Khaled

doi:10.1016/j.autcon.2010.11.001

Cited by 45 publications

(14 citation statements)

References 17 publications

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“…Publications regarding multi-objective facility layouts in real-world applications include Xu and Li (2012), Khalafallah and El-Rayes (2011), and Gimelli and Muccillo (2013). Xu and Li (2012) proposed a fuzzy random multi-objective decisionmaking model based on the multi-objective particle swarm optimization algorithm for a hydropower construction project in China; Khalafallah and El-Rayes utilized a multi-objective genetic algorithm (MOGA) to optimize multiple conflicting planning objectives for an airport project; and Gimelli and Muccillo (2013) analyzed the conflicting objectives of primary energy saving and simple payback through the application of MOGA II.…”

Section: Multi-objective Facility Layoutmentioning

confidence: 99%

Dynamic Facility Layout With Multi-Objectives

Chen

2014

Asia Pac. J. Oper. Res.

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A problem in multi-objective dynamic facility layout is achieving distance-and adjacency-based objectives for arranging facility layouts across multiple time periods. As a non-deterministic polynomial time-hard problem, it resembles the quadratic assignment problem (QAP), which can be solved through meta-heuristics such as ant colony optimization (ACO). This study investigates three multi-objective approaches coupled with ACO to solve this problem. As the experimental design, we apply the proposed methods to solve the dynamic facility layout problem (DFLP), multi-objective facility layout problem, and multi-objective DFLP based on data sets from the literature to test the quality of the solution. The results show that the proposed methods are effective for solving the problem.

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Section: Multi-objective Facility Layoutmentioning

confidence: 99%

Dynamic Facility Layout With Multi-Objectives

Chen

2014

Asia Pac. J. Oper. Res.

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“…This is the most commonly used approach in previous studies (e.g., Zouein et al 2002;Moselhi et al 2004;El-Rayes and Khalafallah 2005;Easa et al 2006;Hammad et al 2007;Easa and Hossain 2008;El-Rayes and Said 2009;Ning et al 2010;Khalafallah and El-Rayes 2011;Sadeghpour 2011, 2013a) (Fig. 3a and 3b).…”

Section: Approximate Geometrymentioning

confidence: 99%

“…Here, the size of the grid unit is selected such that it can fit the largest object. In a more advanced form of grid representation, an object can occupy multiple grid cells (e.g., Osman et al 2003;Ning et al 2010;Khalafallah and El-Rayes 2011). Using multiple grids allow a more realistic representation of the size of the object in the search process.…”

Section: Grid Systemmentioning

confidence: 99%

The constructs of site layout modeling: an overview

Sadeghpour

Andayesh

2015

Can. J. Civ. Eng.

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Abstract:The efficient planning of site space through the course of a construction project is referred to as site layout planning. Due to its impact on safety, productivity and security on construction sites, several site layout planning models have been developed in the past decades. These models have the common aim of generating best layouts considering the defined constraints and conditions. However, the underlying assumptions that were made during the development of these models seem disparate and often implicit. This study provides an overview of the existing models and aims to draw a holistic view of variables that have been considered at different levels of detail and using different approaches in the site layout literature. Through close examination and comparative analysis of existing models, this study identifies the components that need to be considered for site layout modeling, referred to as constructs. Possible approaches that can be used to realize each construct are presented, and the advantages and disadvantages of these approaches are discussed. It is hoped that this study contributes to a better understanding of site layout modeling, and provide an outline for the development of new site layout planning models.Key words: construction site planning, site layout modeling, modeling constructs, site management, optimization models.Résumé : La planification de l'agencement d'un espace défini dans le cadre d'un chantier de construction est appelée « plan d'aménagement de site ». En raison de l'impact de ce dernier sur la sécurité, la productivité et la sûreté des sites de construction, de nombreux modèles de plans d'aménagement de site ont été développés au cours des dernières décennies. Ces modèles ont pour objectif commun de concevoir des aménagements optimaux en tenant compte de contraintes et de conditions précises. Cependant, les hypothèses de base émises lors de l'élaboration de ces modèles semblent nombreuses et souvent implicites. La présente étude fournit un aperçu des modèles existants et a pour but d'offrir une vision globale des variables qui ont été étudiées à différents niveaux de détail et sous diverses approches dans la littérature traitant de l'aménagement de site. Grâce à un examen attentif et à une analyse comparative des modèles existants, le présent article identifie les composants, nommés « structures », à prendre en compte dans la modélisation de l'aménagement de site. L'article décrit également les différentes approches pouvant être adoptées pour créer chaque structure ainsi que les avantages et désavantages de ces approches. Il est à espérer que la présente étude contribuera à une meilleure compréhension de la modélisation de l'aménagement de site et constituera un point de départ à l'élaboration de nouveaux modèles de plans d'aménagement de site. [Traduit par le Rédaction] Mots-clés : plan de site de construction, modélisation d'aménagement de site, structures de modélisation, gestion de site, modèles d'optimisation.

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“…To solv roposed using dynamic programing in [12] or a Mu GA) in [13]. In [14], multi-objective optimization for ace is proposed. And in [15] and [16], the integer uling and facilities design is solved d at a point of view about multilevel optimization, the ion is proposed in [17].…”

Section: Introductionmentioning

confidence: 99%

Multi-Level and Multi-Objective Design Methodology of Taxiways for Large Airports

Yahagi

Kariya

Takehisa

et al. 2012

JMTL

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In this paper, we propose a method to expand taxiways at large airports that shortens taxiing time and reduces costs. To ease congestion at airports, expanding taxiways is needed. But the exorbitant cost of expansion dictates the discreet selection of expanded taxiways. Determining expanded taxiways is a multilevel and multi-objective optimization problem containing 1-0 integer problem and routing problem. However, little research on this topic is available. In this paper, we propose an algorithm to calculate Pareto solutions applying a Multi-Objective Genetic Algorithm (MOGA) and Ant Colony Optimization (ACO). The proposed method is twice as accurate as other methods, and solutions calculated by proposed method are available when flight schedules are disturbed

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Automated multi-objective optimization system for airport site layouts

Cited by 45 publications

References 17 publications

Dynamic Facility Layout With Multi-Objectives

Dynamic Facility Layout With Multi-Objectives

The constructs of site layout modeling: an overview

Multi-Level and Multi-Objective Design Methodology of Taxiways for Large Airports

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