An Exact Algorithm for Weighted-Mean Trimmed Regions in Any Dimension
نویسندگان
چکیده
منابع مشابه
MaxSolver: An efficient exact algorithm for (weighted) maximum satisfiability
Maximum Boolean satisfiability (max-SAT) is the optimization counterpart of Boolean satisfiability (SAT), in which a variable assignment is sought to satisfy the maximum number of clauses in a Boolean formula. A branch and bound algorithm based on the Davis-Putnam-Logemann-Loveland procedure (DPLL) is one of the most competitive exact algorithms for solving max-SAT. In this paper, we propose an...
متن کاملAn Exact Algorithm for the Mode Identity Project Scheduling Problem
In this paper we consider the non-preemptive variant of a multi-mode resource constrained project scheduling problem (MRCPSP) with mode identity, in which a set of project activities is partitioned into disjoint subsets while all activities forming one subset have to be processed in the same mode. We present a depth-first branch and bound algorithm for the resource constrained project schedulin...
متن کاملAn Algorithm for Mining Weighted Dense Maximal 1-Complete Regions
We propose a new search algorithm for a special type of subspace clusters, called maximal 1-complete regions, from high dimensional binary valued datasets. Our algorithm is suitable for dense datasets, where the number of maximal 1-complete regions is much larger than the number of objects in the datasets. Unlike other algorithms that find clusters only in relatively dense subspaces, our algori...
متن کاملAn algorithm for computing exact least-trimmed squares estimate of simple linear regression with constraints
The least-trimmed squares estimation (LTS) is a robust solution for regression problems. On the one hand, it can achieve any given breakdown value by setting a proper trimming fraction. On the other hand, it has √ n-consistency and asymptotic normality under some conditions. In addition, the LTS estimator is regression, scale, and a6ne equivariant. In practical regression problems, we often nee...
متن کاملA Multi-Objective Particle Swarm Optimization Algorithm for a Possibilistic Open Shop Problem to Minimize Weighted Mean Tardiness and Weighted Mean Completion Times
We consider an open shop scheduling problem. At first, a bi-objective possibilistic mixed-integer programming formulation is developed. The inherent uncertainty in processing times and due dates as fuzzy parameters, machine-dependent setup times and removal times are the special features of this model. The considered bi-objectives are to minimize the weighted mean tardiness and weighted mean co...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Statistical Software
سال: 2012
ISSN: 1548-7660
DOI: 10.18637/jss.v047.i13