Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: combinatorial structures

Sortuj według:

Ogranicz wyniki do:

A note on hardness of multiprocessor scheduling with scheduling solution space tree

Dwibedy Debasis, Mohanty Rakesh

Computer Science

2023

T. 24 (1)

53--74

We study the hardness of the non-preemptive scheduling problem of a list of independent jobs on a set of identical parallel processors with a makespan minimization objective. We make a maiden attempt to explore the combinatorial structure of the problem by introducing a scheduling solution space tree (SSST) as a novel data structure. We formally define and characterize the properties of SSST through our analytical results. We show that the multiprocessor scheduling problem is N P-complete with an alternative technique using SSST and weighted scheduling solution space tree (WSSST) data structures. We propose a non-deterministic polynomial-time algorithm called magic scheduling (MS) based on the reduction framework. We also define a new variant of multiprocessor scheduling by including the user as an additional input parameter, which we called the multiuser multiprocessor scheduling problem (MUMPSP). We also show that MUMPSP is N P-complete. We conclude the article by exploring several non-trivial research challenges for future research investigations.

Boys-and-girls Birthdays and Hadamard Products

Bodini O., Gardy D., Roussel O.

Fundamenta Informaticae

2012

Vol. 117, nr 1-4

85-101

Boltzmann models from statistical physics, combined with methods from analytic combinatorics, give rise to efficient and easy-to-write algorithms for the random generation of combinatorial objects. This paper proposes to extend Boltzmann generators to a new field of applications by uniformly sampling a Hadamard product. Under an abstract real-arithmetic computationmodel, our algorithm achieves approximate-size sampling in expected time O(n.n) or O(n σ) depending on the objects considered, with . the standard deviation of smallest order for the component object sizes. This makes it possible to generate random objects of large size on a standard computer. The analysis heavily relies on a variant of the so-called birthday paradox, which can be modelled as an occupancy urn problem.