Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Using genetic algorithms in optimizing construction material delivery schedules
–
To develop a systematic procedure and a computerized tool for optimizing the delivery and inventory of materials, as part of a comprehensive material management system in construction projects.
A newly devised approach that employs genetic algorithms (GAs) for the optimization of material delivery schedules and their associated inventory control is presented. The approach is based on the project material requirement plans, and employs an objective function that minimizes the total costs associated with material deliveries. Furthermore, the computer system developed is used to examine and validate the adopted approach.
GA proved to be a satisfactory approach for optimizing material delivery schedules and its associated inventory levels. The selected case study particularly showed the system to produce material delivery plans that have reduced costs compared with their actual counterparts. Also, the computer processing time for developing the optimized plans was rather minimal, which promote its practical use.
The paper addresses one part of the comprehensive material management system; that is the optimization of the material delivery schedules and inventory control. Other future publications by the same authors will address the issues of probabilistic lead time calculations and development of material ordering schedules.
The paper partially fulfills a long-sought research need for developing comprehensive material management systems specifically tailored to construction projects. The system takes into account several parameters that are not typically incorporated in the economic order quantity models for material management. Furthermore, practicality of the introduced system is augmented by the fact that it is interlinked with one of the most commonly used scheduling software.
Using genetic algorithms in optimizing construction material delivery schedules
–
To develop a systematic procedure and a computerized tool for optimizing the delivery and inventory of materials, as part of a comprehensive material management system in construction projects.
A newly devised approach that employs genetic algorithms (GAs) for the optimization of material delivery schedules and their associated inventory control is presented. The approach is based on the project material requirement plans, and employs an objective function that minimizes the total costs associated with material deliveries. Furthermore, the computer system developed is used to examine and validate the adopted approach.
GA proved to be a satisfactory approach for optimizing material delivery schedules and its associated inventory levels. The selected case study particularly showed the system to produce material delivery plans that have reduced costs compared with their actual counterparts. Also, the computer processing time for developing the optimized plans was rather minimal, which promote its practical use.
The paper addresses one part of the comprehensive material management system; that is the optimization of the material delivery schedules and inventory control. Other future publications by the same authors will address the issues of probabilistic lead time calculations and development of material ordering schedules.
The paper partially fulfills a long-sought research need for developing comprehensive material management systems specifically tailored to construction projects. The system takes into account several parameters that are not typically incorporated in the economic order quantity models for material management. Furthermore, practicality of the introduced system is augmented by the fact that it is interlinked with one of the most commonly used scheduling software.
Using genetic algorithms in optimizing construction material delivery schedules
Georgy, Maged (Autor:in) / Basily, Sameh Y. (Autor:in)
Construction Innovation ; 8 ; 23-45
18.01.2008
23 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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