2022
DOI: 10.1108/jfm-10-2021-0129
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Multiobjective and multivariable optimization for earthmoving equipment

Abstract: Purpose Efficient management of earthmoving equipment is critical for decision-makers in construction engineering management. Thus, the purpose of this paper is to prudently identify, select, manage and optimize the associated decision variables (e.g. capacity, number and speed) for trucks and loaders equipment to minimize cost and time objectives. Design/methodology/approach This paper addresses an innovative multiobjective and multivariable mathematical optimization model to generate a Pareto-optimality se… Show more

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Cited by 23 publications
(9 citation statements)
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“…As a result, regardless of the pipe diameter, the optimal pipe thickness rose (nearly doubles) as the soil depth increases from 2.4 m to 20 m. This example shows how designers and practitioners utilize Equation (1) to determine the best reinforced concrete pipeline for a given pipe geometry and soil depth. Thus, in construction projects, providing decision-support tools using machine and deep learning approaches is vital [37][38][39][40][41][42][43][44][45][46][47][48].…”
Section: Designers Aid In Selecting Optimum Rc Pipeline Thicknessmentioning
confidence: 99%
“…As a result, regardless of the pipe diameter, the optimal pipe thickness rose (nearly doubles) as the soil depth increases from 2.4 m to 20 m. This example shows how designers and practitioners utilize Equation (1) to determine the best reinforced concrete pipeline for a given pipe geometry and soil depth. Thus, in construction projects, providing decision-support tools using machine and deep learning approaches is vital [37][38][39][40][41][42][43][44][45][46][47][48].…”
Section: Designers Aid In Selecting Optimum Rc Pipeline Thicknessmentioning
confidence: 99%
“…The data for non-financial barriers were not as exhaustive as the financial data, potentially skewing the impact of these factors in the proposed model. While the study used the most recent data, real-time data could offer a more dynamic and current picture [ [52] , [53] , [54] , [55] , [56] , [57] , [58] ].…”
Section: Discussionmentioning
confidence: 99%
“…Several academics have attempted to anticipate green construction costs; however, their conclusions were limited to a single location since only a few relevant features were evaluated [2,3,63]. Such problems prove that decision-making tools are in great demand in the construction industry [64][65][66][67][68][69].…”
Section: Discussionmentioning
confidence: 99%