Abstract
This paper presents a constraint-based genetic algorithm dedicated to optimizing earthmoving operations. The algorithm aims to minimize the total cost of earthmoving operations, accounting for efficient use of the selected equipment fleet. Total cost, duration, and utilization of the equipment fleets involved are estimated via computer simulation and passed to the developed algorithm to optimize fleet selection. Users specify the lower limits of equipment utilization as constraints that guide the algorithm search. The developed algorithm has powerful features: (i) it runs in canonical and genitor forms and (ii) it allows normalization of fitness values of chromosomes using three methods, namely inversion, linear ranking, and nonlinear ranking normalization. The algorithm supports roulette wheel and tournament methods for random selection of chromosomes. Crossover can be applied in a discrete or arithmetic form. In addition, the algorithm performs its computations in an efficient manner by elite best-fit chromosome in all generations and by storing chromosome information in its database. The proposed algorithm is explained in the context of a numerical example to clarify its useful features.Key words: earthmoving, equipment selection, optimization, genetic algorithms, computer simulation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
