In this exposition, we give a overview of the GCT approach to solve fundamental lower bound problems in algebraic models of computation. 1.1 Lower bound problems Consider a polynomial f(~x) ∈ Z[~x] with integral coefficients. The non-uniform version of the P v/s NP problem, prescribes a specific such f and asks if it can be shown not to have polynomial size arithmetic circuits over F2. The char...

In this paper a computational mode is presented base on DNA molecules. This model incorporates the theoretical simulation of the principal operations in genetic algorithms. It defines the way of coding of individuals, crossing and the introduction of the individuals so created into the population. It resolves satisfactorily the problems of fitness coding. It shows also the model projection for ...

In today’s competitive market place, companies seek an efficient structure of supply chain so as to provide customers with highest value and achieve competitive advantage. This requires a broader perspective than just the borders of an individual company during a supply chain. This paper investigates an aggregate production planning problem integrated with distribution issues in a supply chain ...

This paper proposes a novel, bi-objective mixed-integer mathematical programming for an open shop scheduling problem (OSSP) that minimizes the mean tardiness and the mean completion time. To obtain the efficient (Pareto-optimal) solutions, a fuzzy multi-objective decision making (fuzzy MODM) approach is applied. By the use of this approach, the related auxiliary single objective formulation can...

In this study, we improved the variable neighborhood search (VNS) algorithm for solving uncapacitated multilevel lot-sizing (MLLS) problems. The improvement is two-fold. First, we developed an effective local search method known as the Ancestors Depth-first Traversal Search (ADTS), which can be embedded in the VNS to significantly improve the solution quality. Second, we proposed a common and e...

Logistic regression with `1 regularization has been proposed as a promising method for feature selection in classification problems. In this paper we describe an efficient interior-point method for solving large-scale `1-regularized logistic regression problems. Small problems with up to a thousand or so features and examples can be solved in seconds on a PC; medium sized problems, with tens of...

this paper presents a genetic algorithm (ga) for solving a generalized model of single-item resource-constrained aggregate production planning (app) with linear cost functions. app belongs to a class of pro-duction planning problems in which there is a single production variable representing the total production of all products. we linearize a linear mixed-integer model of app subject to hiring...