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Non-disjoint Multi-agent Scheduling Problem on Identical Parallel Processors

机译:相同并行处理器上的不相交多智能体调度问题

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Scheduling problems in which agents (users, customers, application masters, resource manager, etc.) have to share the same set(s) of resources are at the frontier of combinatorial optimization and cooperative game theory. This paper deals with scheduling problems arising when two agents, each with a set of nonpreemptive jobs, compete to perform their respective jobs on two common identical parallel machines. Each agent aims at minimizing a certain objective function that depends on the completion times of its jobs only. The objective functions we consider in our study are makespan and number of tardy jobs. The agents may share some jobs and this problem is called non-disjoint multi-agent scheduling problem. Finding the optimal solution for one agent with a constraint on the other agent's cost function is known to be NP-hard. To obtain best compromise solutions for each agent, we propose polynomial and pseudo-polynomial heuristics. Two mixed integer linear programming models are developed to calculate exact non-dominated solutions. Experimental results are conducted to measure the solutions quality given by heuristics.
机译:代理(用户,客户,应用程序主控,资源管理器等)必须共享相同资源集的调度问题处于组合优化和合作博弈理论的前沿。本文处理当两个具有各自非抢占性工作的代理竞争在两个相同的相同并行机上执行各自的工作时出现的调度问题。每个代理程序旨在最小化仅取决于其工作完成时间的某个目标功能。我们在研究中考虑的目标功能是制造时间和迟到的工作数量。代理可以共享一些工作,此问题称为不相交的多代理调度问题。对于一个代理商,寻找对另一代理商的成本函数有约束力的最佳解决方案,这是已知的NP-难问题。为了获得针对每个代理的最佳折衷解决方案,我们提出了多项式和伪多项式启发式方法。开发了两个混合整数线性规划模型来计算精确的非支配解。进行实验结果以衡量启发式方法给出的解决方案质量。

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