[PDF] Top 20 Multiprocessor Scheduling Using Parallel Genetic Algorithm

... tasks scheduling is the most challenging problem regarding parallel ...inappropriate scheduling will reduce or even abort the utilization of the true potential of the ...time. Genetic ... See full document

... various parallel algorithms are developed and ported to parallel computer ...the parallel algorithms should be designed directly by programmer, which makes it hard for general programmer to ... See full document

... as Genetic Algorithm based routing algorithm, which is highly scalable and insensitive to variations in network ...coarse-grained parallel genetic algorithm to solve the shortest ... See full document

... factory using different types of AGVs, with different hardware and software, making the com- munication between AGVs more difficult and, in case of malfunction, the AGVs where hard to substitute by another without ... See full document

... Logendran and Subur [2004] studied the UPMSP, with job splitting and distinct release dates for jobs and machines, to minimize total weighted tardiness. The authors present a MIP model using assignment and ... See full document

... classical multiprocessor scheduling problem is one of the well-investigated problems of the last ...m parallel, identical machines in order to minimize the ...greedy algorithm has a ... See full document

... The minimum execution time of a group of tasks assigned to a work order, since tasks are sequential, is given by the sum of all the assigned tasks. This execution time can be bigger if a worker, or set of workers, are ... See full document

... the parallel running of test of multiple cores increases the power ...the scheduling the cores with the test time, power, test access mechanism and bandwidth constraint based on greedy ...this ... See full document

... grid scheduling complicated, so the deterministic algorithms will not necessarily be efficient to solve these kinds of ...as Genetic Algorithm (GA). The simplicity and parallel nature of ... See full document

... railway scheduling problem has received considerable attention from both practitioners and ...by using novel heuristic optimization approaches in the multi-objective passenger railway scheduling ... See full document

... In this paper we solve Time-Cost trade-off project, in a way that sees decision maker preferences and cares about resource restriction simultaneously. Cause of being a part of NP-hard questions we use a meta-initiative ... See full document

... Nowadays, electricity bus becomes an important traffic transfer in Naresuan University. An increasing proportion in passenger causes the problem of scheduling. In this paper, an appropriate traffic transportation ... See full document

... of scheduling a manipulator robot, one of the main objectives is to find the optimum sequence of the manipulators trip visiting a several ...order using the less amount of ... See full document

... A mixed-integer linear programming (MILP) model is proposed to formulate the problem under study. The objective is to minimize the total tardiness in order to maximize on-time delivery performance. A special case of the ... See full document

... λ. It also considers one cluster, but this time, the cluster main direction is not fixed but uniformly distributed around the space. The cluster has the same angle spread of other simulations but is not plotted in the ... See full document

... the algorithm design ...our algorithm can fork a series of sub-processes to find attractors using the attractors found in the first ...The parallel version of the algorithm is described ... See full document

... shop scheduling problem may be described as follows :Given‘n’ number of jobs, each comprises several operations that must be processed on ‘m’ number of ...schedule. Genetic algorithms are a random search ... See full document

... developed parallel version of Michalewicz’s Genocop III, Genetic Algorithm (GA) searching technique to optimize the coil geometry of an eddy current non-destructive testing probe ...computed ... See full document

... Meta-heuristics is used to solve with the computationally hard optimization problems. Meta- heuristics consist of a high level algorithm that guides the search using other particular methods. Meta- ... See full document

... (SA), Genetic Algorithms (GAs) and Tabu Search (TS) have been proposed to find the near optimal solutions for the problem of scheduling jobs on a single ma- chine with a common due date [6, 7, 9] and ...TS ... See full document