Survey of Various Meta-Heuristic Algorithms for Parallel Job Scheduling
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Abstract
This paper presents an overview of various nature-inspired optimization algorithms for scheduling problems. Nature is a vast source of inspiration to solve complex problems (NP-hard) in computer science as it shows extremely diverse, dynamic, robust, complex and fascinating techniques. It helps to find the optimal solution in order to solve the problem keeping perfect balance among its components. Nature inspired algorithms are meta-heuristics which are motivated by the nature in order to solve various optimization problems. For the past decades, great research efforts has been concentrated on these techniques. The surprising results increase the scope and practicality of these meta-heuristic techniques exploring new areas of application and more opportunities in computing.
Keywords: Parallel computing, multi-objective optimization, scheduling, co-allocation, multi-clusters, meta-heuristics
Keywords: Parallel computing, multi-objective optimization, scheduling, co-allocation, multi-clusters, meta-heuristics
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