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Review of the research landscape of multi-criteria evaluation and bench- marking processes for many-objective optimisation methods: coherent taxonomy, challenges and recommended so...
Published 2020“…Evaluation and benchmarking of many-objective optimization (MaOO) methods are complicated. The rapid development of new optimization algorithms for solving problems with many objectives has increased the necessity of developing performance indicators or metrics for evaluating the performance quality and comparing the competing optimization algorithms fairly. …”
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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Thesis -
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Crosstalk-Free Scheduling Algorithms for Routing in Optical Multistage Interconnection Networks
Published 2009“…Based on Zero algorithms, a Modified Zero algorithm is developed to achieve a crosstalk-free version of the algorithm. …”
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COMPARATIVE PERFORMANCE OF SOME HYBRID HEURISTICS SCHEDULING ALGORITHMS BASED ON SLTR AND DEADLINE FOR COMPUTATIONAL GRID
Published 2013“…Research on Grid scheduling focuses in solving three challenges: finding a good algorithm, automating the process, and developing a scalable, robust and efficient scheduling mechanism. …”
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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
Published 2022“…It is difficult and challenging to develop an algorithm that can produce consistent near-optimal solutions even after many runs, average near-optimal solutions that have the least difference in magnitude, broader Pareto set, and iii achieve near-optimal solutions but highly sought after if it is commercially viable. …”
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Final Year Project / Dissertation / Thesis -
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Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions
Published 2025“…Many clustered routing algorithms have been developed to address various issues like energy efficiency, network lifetime, and hotspot problems. …”
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Ontology matching: in search of challenges ahead
Published 2015“…This paper presents key features and challenges for the development of the next generation ontology matcher. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In order to address the above mentioned challenges, this study is devoted towards the development of a clusterer and a clustering ensemble learning method based on incremental genetic algorithms addressing group unlabeled samples. …”
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Assembly sequence optimization using the bees algorithm
Published 2022“…In this study, the assembly sequence of a product was optimized by applying an algorithm known as the Bees Algorithm. To assess the performance of this Algorithm, the results are compared with results found by other algorithms. …”
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Book Chapter -
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Published 2019“…One of the major challenges and difficulties to generate optimal operation rule for dam and reservoir operation are how efficient the optimization algorithm to search for the global optimal solution and the time-consume for convergence. …”
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Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes
Published 2025“…The research leverages Artificial Intelligence (AI)-based Genetic Algorithms (GA) and game theory to address critical challenges in resource allocation. …”
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Thesis -
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A review on the applications of PSO-based algorithm in demand side management: Challenges and opportunities
Published 2023“…Therefore, this paper reviewed the application of the PSO-based algorithm in DSM fields with some constraints and discussed the challenges from the previous work. …”
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Crossover and mutation operators of genetic algorithms
Published 2017“…Due to lower diversity in a population, it becomes challenging to locally exploit the solutions. In order to resolve these issues, the focus is now on reaching equilibrium between the explorative and exploitative features of GA. …”
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Design issues and challenges of an FPGA-based orthogonal matching pursuit implementation for compressive sensing reconstruction
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Conference or Workshop Item -
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Sub-route reversal repair mechanism and differential evolution for urban transit network design problem
Published 2017“…The problem is characterized by huge search space with multiobjective in nature, and it is considered as one of the most challenging combinatorial optimization problems. Due to the NP-hard nature of the UTNDP, the evaluation of candidate solution is challenging and time consuming, in which many potential solutions are discarded on the grounds of infeasibility. …”
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Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms
Published 2012“…Thus, the task of designing a robot can be considered very demanding and extremely challenging. In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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Research Report -
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Crossover and mutation operators of genetic algorithms
Published 2017“…Due to lower diversity in a population, it becomes challenging to locally exploit the solutions. In order to resolve these issues, the focus is now on reaching equilibrium between the explorative and exploitative features of GA. …”
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