2007/01/01 by Leah Epstein, Epstein, Leah, Rob van Stee +1
Computer Science · Decision Sciences · Engineering · #Auction Theory and Applications #Optimization and Search Problems #Scheduling #Scheduling and Optimization Algorithms #algorithmic mechanism design #maximizing minimum load
paper · doi:10.4230/dagsemproc.07261.10
openalex publication_date 2007/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We consider the problem of maximizing the minimum load for machines that are controlled by selfish agents, who are only interested in maximizing their own profit. Unlike the classical load balancing problem, this problem has not been considered for selfish agents until now. For a constant number of machines, m, we show a monotone polynomial time approximation scheme (PTAS) with running time that is linear in the number of jobs. It uses a new technique for reducing the number of jobs while remaining close to the optimal solution. We also present an FPTAS for the classical machine covering problem, i.e., where no selfish agents are involved (the previous best result for this case was a PTAS) and use this to give a monotone FPTAS. Additionally, we give a monotone approximation algorithm with approximation ratio min(m,(2+eps)s1/sm) where eps>0 can be chosen arbitrarily small and si is the (real) speed of machine i. Finally we give improved results for two machines.