《Incorporating Practicability into Genetic Algorithm-Based Time-Cost Optimization》.pdf

Incorporating Practicability into Genetic Algorithm-Based Time-Cost Optimization Bryan Christopher Que1 Abstract: Optimization problems in construction scheduling, such as time-cost optimization, can be effectively solved using genetic . d algorithms GAs. This paper presents an approach that makes GA-based time-cost optimization viable for real world problems. Practi- e v r cability is incorporated through the integration of a project management system to the GA system. The approach takes advantage of the e s e r powerful scheduling functionality of the project management system in evaluating project completion dates during optimization. The s t h approach ensures that all scheduling parameters, including activity relationships, lags, calendars, constraints, resources, and progress, are g i r l considered in determining the project completion date, thus allowing comprehensive and realistic evaluations to be made during l a ; optimization. y l n o e DOI: 10.1061/ASCE0733128:2139 s u l a n CE Database keywords: Optimization; Scheduling; Construction management; Algorithms; Project management. o s r e p r o F . Introduction Genetic algorithms GAs are a set of tools based on natural E C selection and the mechanisms of population genetics developed S A Optimization problems in construction scheduling are tradition- by John Holland. GAs employ a random yet directed