Minimizing total tardiness on one machine is NP-hard
Mathematics of Operations Research
LSTF: a new scheduling policy for complex real-time tasks in multiple processor systems
Automatica (Journal of IFAC)
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
IEEE Transactions on Computers
Journal of Parallel and Distributed Computing - Problems in parallel and distributed computing: Solutions based on evolutionary paradigms
Hybrid Genetic Algorithms for Scheduling Partially Ordered Tasks in a Multi-Processor Environment
RTCSA '99 Proceedings of the Sixth International Conference on Real-Time Computing Systems and Applications
SSST '96 Proceedings of the 28th Southeastern Symposium on System Theory (SSST '96)
A Proportional-Share Scheduler for Multimedia Applications
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
Optimal Quantization of Periodic Task Requests on Multiple Identical Processors
IEEE Transactions on Parallel and Distributed Systems
Genetic-algorithm-based real-time task scheduling with multiple goals
Journal of Systems and Software - Special issue: Computer systems
Minimum and Maximum Utilization Bounds for Multiprocessor Rate Monotonic Scheduling
IEEE Transactions on Parallel and Distributed Systems
Dynamic Task Scheduling using Genetic Algorithms for Heterogeneous Distributed Computing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 6 - Volume 07
Computers and Operations Research
Journal of Systems and Software
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Genetic algorithm and difference expansion based reversible watermarking for relational databases
Journal of Systems and Software
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Real-time tasks are characterized by computational activities with timing constraints and classified into two categories: a hard real-time task and a soft real-time task. In hard real-time tasks, tardiness can be catastrophic. The goal of hard real-time tasks scheduling algorithms is to meet all tasks' deadlines, in other words, to keep the feasibility of scheduling through admission control. However, in the case of soft real-time tasks, slight violation of deadlines is not so critical. In this paper, we propose a new scheduling algorithm for soft real-time tasks using multiobjective genetic algorithm (moGA) on multiprocessors system. It is assumed that tasks have precedence relations among them and are executed on homogeneous multiprocessor environment. The objective of the proposed scheduling algorithm is to minimize the total tardiness and total number of processors used. For these objectives, this paper combines adaptive weight approach (AWA) that utilizes some useful information from the current population to readjust weights for obtaining a search pressure toward a positive ideal point. The effectiveness of the proposed algorithm is shown through simulation studies.