T
Tarek Y. ElMekkawy
Researcher at Qatar University
Publications - 66
Citations - 1987
Tarek Y. ElMekkawy is an academic researcher from Qatar University. The author has contributed to research in topics: Job shop scheduling & Flow shop scheduling. The author has an hindex of 20, co-authored 62 publications receiving 1650 citations. Previous affiliations of Tarek Y. ElMekkawy include University of Manitoba & University of Windsor.
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Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach
TL;DR: In this article, a particle swarm optimization (PSO)-simulation based approach has been used to tackle the multi-objective optimization problem of hybrid renewable energy systems (HRES) including various generators and storage devices.
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Robust and stable flexible job shop scheduling with random machine breakdowns using a hybrid genetic algorithm
Nasr Al-Hinai,Tarek Y. ElMekkawy +1 more
TL;DR: A two-stage Hybrid Genetic Algorithm is proposed to generate the predictive schedule, which optimizes the primary objective, minimizing makespan in this work, where all the data is considered to be deterministic with no expected disruptions.
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Appointment scheduling of outpatient surgical services in a multistage operating room department
TL;DR: This article addresses the appointment scheduling of outpatient surgeries in a multistage operating room (OR) department with stochastic service times serving multiple patient types with many challenges, such as the limited availability of multiple resources, and the compatibility of patient and surgeon types.
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Hybridized ant colony algorithm for the Multi Compartment Vehicle Routing Problem
TL;DR: A hybridized algorithm which combines local search with an existent ant colony algorithm to solve the Multi Compartment Vehicle Routing Problem is proposed and it was found that the proposed ant colonies algorithm gives better results as compared to the existing ant colony algorithms.
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Optimal design of hybrid renewable energy systems in buildings with low to high renewable energy ratio
TL;DR: In this paper, a simulation-based meta-heuristic approach was developed to determine the optimal size of a hybrid renewable energy system for residential buildings for the purpose of maximizing the renewable energy ratio of buildings and minimizing the total net present cost and CO2 emission for required system changes.