The scheduling problem on a single batching machine with family jobs was proposed.The single batching machine can process a group of jobs simultaneously as a batch.Jobs in the same batch complete at the same time.The ...The scheduling problem on a single batching machine with family jobs was proposed.The single batching machine can process a group of jobs simultaneously as a batch.Jobs in the same batch complete at the same time.The batch size is assumed to be unbounded.Jobs that belong to different families can not be processed in the same batch.The objective function is minimizing maximum lateness.For the problem with fixed number of m families and n jobs,a polynomial time algorithm based on dynamic programming with time complexity of O(n(n/m+1)m)was presented.展开更多
In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batchi...In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batching machine scheduling problem of minimizing the maximum lateness, denoted 1|p-batch|L_(max), a dynamic programming algorithm with time complexity O(n^2) is well known in the literature.Later, this algorithm is improved to be an O(n log n) algorithm. In this note, we present another O(n log n) algorithm with simplifications on data structure and implementation details.展开更多
This paper studies the two-agent scheduling on a bounded parallel-batching machine.In the problem,there are two agents A and B each having their own job sets with the restriction that the processing times of jobs of a...This paper studies the two-agent scheduling on a bounded parallel-batching machine.In the problem,there are two agents A and B each having their own job sets with the restriction that the processing times of jobs of agent B are equal.The jobs of different agents can be processed in a common batch.Moreover,each agent has its own objective function to be minimized.The objective function of agent A is the makespan of its jobs,and the objective function of agent B is the maximum lateness of its jobs.We present a polynomial-time algorithm for finding all Pareto optimal solutions of this two-agent parallel-batching scheduling problem.展开更多
基金National Natural Science Foundation of China(No.70832002)Graduate Student Innovation Fund of Fudan University,China
文摘The scheduling problem on a single batching machine with family jobs was proposed.The single batching machine can process a group of jobs simultaneously as a batch.Jobs in the same batch complete at the same time.The batch size is assumed to be unbounded.Jobs that belong to different families can not be processed in the same batch.The objective function is minimizing maximum lateness.For the problem with fixed number of m families and n jobs,a polynomial time algorithm based on dynamic programming with time complexity of O(n(n/m+1)m)was presented.
基金Supported by NSFC(11571323 11201121)+1 种基金NSFSTDOHN(162300410221)NSFEDOHN(2013GGJS-079)
文摘In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batching machine scheduling problem of minimizing the maximum lateness, denoted 1|p-batch|L_(max), a dynamic programming algorithm with time complexity O(n^2) is well known in the literature.Later, this algorithm is improved to be an O(n log n) algorithm. In this note, we present another O(n log n) algorithm with simplifications on data structure and implementation details.
基金This research was supported in part by the National Natural Science Foundation of China(Nos.11401604,11571323,11701595,11501279)also supported by Program for Interdisciplinary Direction Team in Zhongyuan University of Technology,China.
文摘This paper studies the two-agent scheduling on a bounded parallel-batching machine.In the problem,there are two agents A and B each having their own job sets with the restriction that the processing times of jobs of agent B are equal.The jobs of different agents can be processed in a common batch.Moreover,each agent has its own objective function to be minimized.The objective function of agent A is the makespan of its jobs,and the objective function of agent B is the maximum lateness of its jobs.We present a polynomial-time algorithm for finding all Pareto optimal solutions of this two-agent parallel-batching scheduling problem.