Seiki Kyan

Worst case bound of an LRF schedule for the mean weighted flow-time problem

This paper studies the problem of scheduling a set of n independent tasks on m identical processors so as to minimize mean weighted flow-time. The problem is known to be NP-complete for

Genetic algorithm for sex-fair stable marriage problem

m \geqq 2

A mutual exclusion algorithm for a distributed network of autonomous nodes

and to be NP-complete in the strong sense for m arbitrary.The worst case behavior of a heuristic algorithm which requires time

Finding a feasible schedule on a tree-connected processor system

O(n\log n)

Polynomial time minimum cost path algorithms for acyclic networks of C-depth bridges with piece-wise linear time-varying travel costs and transit delays

is investigated, and it is shown that the mean weighted flow-time obtained by the algorithm does not exceed

Transmission control for time-critical messages in packet-switching communication nets

{{(\sqrt 2 + 1)} / 2} \cong 1.0207

Scheduling jobs on a multiprocessor system with a common memory

times that of an optimal schedule. Moreover the bound

DETERMINISTIC SCHEDULING IN COMPUTER SYSTEMS: A SURVEY

{{(\sqrt 2 + 1)} / 2}

擬似ランダムビット列生成器及びそれを使用するストリーム暗号通信方式ならびに応用としてのパソコン鍵、ＰＣ間暗号化通信、高質度暗号生成器

is best possible.

A Genetic Algorithm for Multiprocessor Scheduling Problems

In this paper we consider a sex-fair matching in the stable marriage problem. The sex-fair stable matching defined in this paper has a property that the sum of the partners rank of each man in his preference list is as close as possible to the sum of the partners rank of each woman in her preference list. We transform the sex-fair marriage problem into a graph problem which is suitable for a genetic algorithm. We propose a genetic algorithm for the sex-fair stable matching. The transformation into the graph problem makes application of the GA easier and effective. Computer experiments show the effectiveness of the proposed genetic algorithm.