Integrating Messy Genetic Algorithms and Simulation to Optimize Resource Utilization

Abstract

This article presents a mechanism for integrating messy genetic algorithms (MGAs) and a discrete event simulation technique to facilitate the simulation of optimal resource utilization to enhance system performance, such as in relation to the production rate or unit cost. Various resource distribution modeling scenarios were tested in simulation to determine their system performances. MGA operations were then applied in the selection of the best resource utilization schemes based on those performances. A case study showed that this new modeling mechanism, along with the implemented computer program, could not only ease the process of developing optimal resource utilization, but could also improve the system performance of the simulation model.

Using classification techniques to recognize patterns of resource utilization in organizations

“…Research Main contribution Group 1: application of models to analyze resource utilization Majumdar 1 Applying DEA to compare resource utilization efficiency among firms in the telecommunications industry Gimenez-Garcia et al 2 Specifying additional resources of inefficient units in the networked organizations Zahraie and Tavakolan 3 Developing an optimization model to support the balance among cost, time and resource utilization of the projects Leung and Chan 4 Presenting a model to maximize physical resource utilization of the companies Mar-Molinero et al 5 Developing a model for optimal resource allocation in the organizations Gong and Tang 6 Presenting a model to achieve efficient use of renewable resources Patrick and Puterman 7 Proposing a method to minimize unused capacity Cheng et al 8 Examining a number of resource types, such as energy carriers in cloud manufacturing systems Tao et al 9 Proposing a method to increase resource utilization in service transaction chains Davidson and Williams 10 Applying resource optimization models in the plastics industry Group 2: developing frameworks for resource utilization Orabi et al 11 Proposing an integrated framework for optimal resource allocation in projects Cheng and Yan 12 Developing an approach for optimal resource utilization to increase performance measures Lam et al 13 Developing a knowledge-based performance measurement system (KPMS) aimed to improve physical resources utilization Kandil and El-Rayes 14 Proposing a framework for efficient resource utilization in largescale construction projects Kyobe 15 Specifying major challenges of efficient IT resource utilization Group 3: calculation of resource utilization efficiency measures Miller and Ross 16 Calculation of managerial, scale and programmatic efficiency measures of firm resources Yan and Du 17 Proposing measures to analyze external and internal human resource utilization Brandi et al 18 Proposing appropriate estimators for resource consumption Vanhoucke and Debels 19 Investigating effects of the specified factors on the resource utilization of the projects DEA: data envelopment analysis; IT: information technology.…”

Predicting the Duration of Concrete Operations Via Artificial Neural Network and by Focusing on Supply Chain Parameters

“…This mainly concerned the discrete event simulation (DES) tool but in its recent versions was coupled with heuristic solvers such as GA (Cao et al, 2004, Lu and Lam, 2005, Ming and HoiChing, 2009), Particle Swarm Optimization (PSO) (Lu et al, 2006, Wu et al, 2005 and real GPS data of trucks (Lu et al, 2007) in order to make a more powerful tool. Feng and Wu (2006) and Cheng and Yan (2009) had a similar approach by integrating DES with a fast messy GA algorithm. Silva et al (2005) compared GA with Ant Colony Optimization (ACO) and suggested a GA-ACO method for solving RMC problems.…”

Developing Crew Allocation System for the Precast Industry Using Genetic Algorithms

“…al., 2007), electrical transmission towers (Mathakari et. al., 2007), (Cheng et. al., 2009), highway alignment optimization (Kang et.…”