This note studies the learnability of ordered binary decision diagrams (obdds). We give a polynomial-time algorithm using membership and equivalence queries that nds the minimum obdd for the target respecting a given ordering. We also prove that both types of queries and the restriction to a given ordering are necessary if we want minimality in the output, unless P=NP. If learning has to occur ...

Many procedures have been proposed to compute the nonparametric maximum likelihood estimates (NPMLEs) of survival functions under various stochastic ordering constraints. Each of the existing procedures is applicable only to a specific type of stochastic order constraint and often hard to implement. In this paper, we describe a method for computing the NPMLEs of survival functions, based on geo...

The metabolic syndrome has become a significant problem in Asian countries recently due to the change in dietary habit and life style. Bayesian networks provide a robust formalism for probabilistic modeling, so they have been used as a method for prognostic model in medical domain. Since K2 algorithm is influenced by an input order of the attributes, optimization of BN attribute ordering is stu...

In this paper we prove some stochastic comparisons results for progressive type II censored order statistics. The problem of stochastically comparing concomitants of the two progressive type II censored order statistics with possibly different schemes, under different kinds of dependence between X and Y is considered and it is proved that if Y is stochastically increasing (decreasing) in X, ...

Some well-known VLSI interconnect optimizations problems for timing, power and cross-coupling noise immunity share a property that enables mapping them into a specialized Linear Ordering Problem (LOP). Unlike the general LOP problem which is NP-complete, this paper proves that the specialized one has a closed-form solution. Let f (x, y) :R2 →R be symmetric, non-negative, defined for x ≥ 0 and y...

We present two algorithms within the framework of the Ant Colony Optimization (ACO) metaheuristic. The first algorithm seeks to increase the exploration bias of Gambardella et al.’s (2012) Enhanced Ant Colony System (EACS) model, a model which heavily increases the exploitation bias of the already highly exploitative ACS model in order to gain the benefit of increased speed. Our algorithm aims ...

We introduce an algorithm design technique for a class of combinatorial optimization problems with concave costs. This technique yields a strongly polynomial primal-dual algorithm for a concave cost problem whenever such an algorithm exists for the fixedcharge counterpart of the problem. For many practical concave cost problems, the fixed-charge counterpart is a well-studied combinatorial optim...

This study aims to deal with a more realistic combined problem of project scheduling and material ordering. The goal is to minimize the total material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject to some constraints. The problem is first mathematically modelled. Then a hybrid simulated annealing and genetic algorithm is...