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Task scheduling is critical for obtaining a high performance schedule in heterogeneous computing systems (HCS) and searching an optimal scheduling solution has been shown to be NP-complete. In this paper, a hybrid heuristicgenetic algorithm with adaptive parameter (HGAAP) is proposed by combining a heuristic scheduling algorithm and a genetic algorithm. An existing common heuristic scheduling algorithm...
A hybrid optimization algorithm is proposed for Job-Shop scheduling problem, which is based on the combination of adaptive genetic algorithm and improved ant algorithm. The algorithm gets the initial pheromone distribution using adaptive genetic algorithm at first, then runs improved ant algorithm. The algorithm utilizes the advantages of the two algorithms and overcomes their disadvantages. Experimental...
Master thesis defense scheduling problem is a real-world practical problem that arises from the Vietnamese Universities. In this paper, we give the formulation of the problem based on realistic requirements. We then show that the considered problem is NP-hard and propose a genetic algorithm for solving it. We experiment the proposed algorithm on the real problem instances taken from Hanoi University...
On the distributed or parallel heterogeneous computing systems, an application is usually decomposed into several independent and/or interdependent sets of cooperating subtasks and assigned to a set of available processors for execution. Heuristic-based task scheduling algorithms consist of the two typical phases of task prioritization and processor selection. However, heuristic-based task scheduling...
The flexible manufacturing system (FMS) is a complex discrete event dynamic system (DEDS). The Petri net is suitable for describing the DEDS, so the Petri net is used to model the FMS. Aiming at the scheduling optimization of the FMS, an improved genetic algorithm (GA) is proposed and applied to the scheduling of the Petri net model. An approximate optimal solution is given. Then a given FMS example...
Increasing delay and power variation has become a major challenge to designing high performance Multiprocessor System-On-Chips (MPSoC) in deep sub-micron technologies. As a result, a paradigm shift from deterministic to statistical design methodology at all levels of the design hierarchy is inevitable. In this paper, we propose a static variation-aware task scheduling and power mode selection algorithm...
The Educational timetabling problem is a common and hard problem inside every educative institution, this problem tries to coordinate Students, Teachers, Classrooms and Timeslots under certain constrains that dependent in many cases the policies of each educational institution. The idea behind hyper-heuristics is to discover some combination of straightforward heuristics to solve a wide range of problems...
Semiconductor wafer fabrication facilities (fabs) cry for optimized dynamic scheduling approach due to its high uncertainty and complexity. A novel intelligent optimized dynamic scheduling method, integrating intelligent sequencing with dynamic dispatching, is proposed (abbreviated as ODC). ODC includes three sub-algorithms, i.e., a Partheno-Genetic Algorithm (PGA) to obtain optimized sequencing plan,...
The resource constrained project scheduling problem is one of the most important issues that project managers have to deal with during the project implementation, as constrained resource availabilities very often lead to delays in project completion and budget overruns. For solving this NP-hard optimization problem, we propose a genetic based hyperheuristic, i.e. an algorithm controlling a set of...
This paper considers a flowshop scheduling problem with synchronous material movement in an automated machining center. This automated machining center consists of a loading/unloading (L/U) station, m processing machines, and a rotary table. The L/U station and the processing machines surround the rotary table which transports jobs between machines. The table rotates to simultaneously move jobs when...
Grid workflow scheduling in large scale e-Business applications is a complex optimization problem which may require consideration of different scheduling criteria to achieve various quality of service (QoS) requirements. Meanwhile, the researches on grid workflow scheduling mainly focus on the constraint of time and cost, the key requirements about trustworthiness aren't considered adequately. Aiming...
This paper presents a dynamic size-based multiobjective genetic algorithm (DSMGA) to solve the crew pairing problem in airline companies. The proposed DSMGA has several features, such as 1) A permutation-based model is proposed rather than the 0-1 set partition model. 2) Instead of pre-assigning a fixed group number of crewmembers, the proposed method can determine it by performing the evolutionary...
Complex applications are describing using work-flows. Execution of these workflows in Grid environments require optimized assignment of tasks on available resources according with different constrains. This paper presents a decentralized scheduling algorithm based on genetic algorithms for the problem of DAG scheduling. The genetic algorithm presents a powerful method for optimization and could consider...
In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with backhauls model. According to the characteristics of model, hybrid genetic heuristic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem; retain the best selection so as to guard the diversity of group. Improved ordinal crossover...
This paper deals with the two-machine flow shop scheduling problem in which the first machine is a batch processing machine (BPM) that can process a number of jobs simultaneously, while the second machine is a discrete processing machine (DPM) that processes jobs one by one. To minimize makespan of the system, we present a mixed integer programming formulation for the problem. Using this formulation,...
Lacking of flexibility in the traditional workshop production, a genetic algorithm is proposed to implement the integration of process planning and production scheduling. In order to implement the optimal scheduling of the flexible workshop production, chromosome crossover and mutation are used to select the processing routes and processing machines. Meanwhile, a performance test about the integration...
The dynamic VPN (DVPN) manager (DVM) works as the autonomous system (AS) administrator in the DVPN system to perform resource scheduling and liaise with the underlying connection management. A novel genetic algorithm based resource scheduling algorithm is proposed; simulation results show that this algorithm is both feasible and efficient for use in DVPN scenarios.
This paper presents a dynamic feedback adaptive scheduling algorithm to deal with the load balance of Super Peers in hybrid P2P network. The algorithm applies the adaptive peers' distribution login request by weighted rotation, and adjusts the Super Peers' scheduling sequence dynamically with genetic algorithms to make the Super Peers load in system tending to a best balanced state.
Multiprocessors have emerged as a powerful computing means for running real-time applications, especially where a uniprocessor system would not be sufficient enough to execute all the tasks. The high performance and reliability of multiprocessors have made them a powerful computing resource. Such computing environment requires an efficient algorithm to determine when and on which processor a given...
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