Parallel machine scheduling problems, which are important discrete optimization problems, may occur in many applications. For example, load balancing in network communication channel assignment, parallel processing in...Parallel machine scheduling problems, which are important discrete optimization problems, may occur in many applications. For example, load balancing in network communication channel assignment, parallel processing in large-size computing, task arrangement in flexible manufacturing systems, etc., are multiprocessor scheduling problem. In the traditional parallel machine scheduling problems, it is assumed that the problems are considered in offline or online environment. But in practice, problems are often not really offline or online but somehow in-between. This means that, with respect to the online problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi-online ones. In this paper, the semi-online problem P2|decr|lp (p>1) is considered where jobs come in non-increasing order of their processing times and the objective is to minimize the sum of the lp norm of every machine’s load. It is shown that LS algorithm is optimal for any lp norm, which extends the results known in the literature. Furthermore, randomized lower bounds for the problems P2|online|lp and P2|decr|lp are presented.展开更多
基金Project supported by the National Natural Science Foundation of China (Nos. 10271110 10301028) and the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE+2 种基金 China Project supported by the National Natural Science Foundation of China (Nos. 10271110 10301028) and the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE China
文摘Parallel machine scheduling problems, which are important discrete optimization problems, may occur in many applications. For example, load balancing in network communication channel assignment, parallel processing in large-size computing, task arrangement in flexible manufacturing systems, etc., are multiprocessor scheduling problem. In the traditional parallel machine scheduling problems, it is assumed that the problems are considered in offline or online environment. But in practice, problems are often not really offline or online but somehow in-between. This means that, with respect to the online problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi-online ones. In this paper, the semi-online problem P2|decr|lp (p>1) is considered where jobs come in non-increasing order of their processing times and the objective is to minimize the sum of the lp norm of every machine’s load. It is shown that LS algorithm is optimal for any lp norm, which extends the results known in the literature. Furthermore, randomized lower bounds for the problems P2|online|lp and P2|decr|lp are presented.
