Search results for "PSA"
showing 10 items of 286 documents
NEONATAL CAPSAICIN TREATMENT DOES NOT PREVENT SPLANCHNIC VASODILATATION IN PORTAL-HYPERTENSIVE RATS
1994
It has been suggested that the peripheral sensory neurons are involved in the splanchnic hemodynamic changes of portal hypertension. Therefore the influence of permanent ablation of sensory neurons by neonatal capsaicin pretreatment (50 mg/kg, subcutaneously) on the development of the hyperdynamic splanchnic circulation in portal-hypertensive rats was studied. In adulthood, portal hypertension was induced with partial portal vein ligation. In study 1, systemic and splanchnic hemodynamics were measured by means of a radiolabeled-microsphere technique in portal-hypertensive rats, under ketamine anesthesia, pretreated with capsaicin or vehicle. Mean arterial pressure, heart rate, cardiac index…
Gastric acid secretory responses induced by peptone are mediated by capsaicin-sensitive sensory afferent neurons
1992
The involvement of capsaicin-sensitive afferent neurons in modulating acid-secretory responses to peptone, a product of protein digestion, has been investigated in the continuously perfused stomach of the urethan-anesthetized rat. Systemic neonatal pretreatment with capsaicin, which destroys primary afferent neurons, does not modify basal levels of acid secretion. Acid responses to intragastric perfusion with isotonic (0.5, 1, and 2.4%) or hypertonic (10 and 20%) solutions of peptone were reduced in capsaicin-treated rats. Intragastric perfusion with hypertonic mannitol (18%) did not stimulate secretion of acid. Systemic capsaicin pretreatment did not modify acid responses to intraperitone…
GRASP with path relinking for the orienteering problem
2014
In this paper, we address an optimization problem resulting from the combination of the well-known travelling salesman and knapsack problems. In particular, we target the orienteering problem, originated in the context of sport, which consists of maximizing the total score associated with the vertices visited in a path within the available time. The problem, also known as the selective travelling salesman problem, is NP-hard and can be formulated as an integer linear program. Since the 1980s, several solution methods for this problem have been developed and applied to a variety of fields, particularly in routing and tourism. We propose a heuristic method—based on the Greedy Randomized Adapt…
The internalisation of foreign distribution and production activities
2001
Abstract This paper, using a logit model applied to a sample of 323 Spanish companies with international activities, analyses the key factors in the creation of sales and production subsidiaries. A high degree of fit between the results and the established hypotheses can be observed. Many interesting findings related to the main streams of entry mode research (Transaction Cost Theory and the Uppsala Model) have been supported. The intangibility and tacit nature of the products/processes involved in the foreign venture have been directly associated to wholly owned sales and production subsidiaries. Moreover, modes of entry used by Spanish firms are adapted as an incremental, experiential lea…
A genetic algorithm for the minimum generating set problem
2016
Graphical abstractDisplay Omitted HighlightsWe propose a novel formulation for the MGS problem based on multiple knapsack.The so-conceived MGS problem is solved by a novel GA.The GA embeds an intelligent construction method and specialized crossover operators.We perform a thorough comparison with regards to state-of-the-art algorithms.The proposal proves to be very competitive, specially for large and hard instances. Given a set of positive integers S, the minimum generating set problem consists in finding a set of positive integers T with a minimum cardinality such that every element of S can be expressed as the sum of a subset of elements in T. It constitutes a natural problem in combinat…
The Multiple Multidimensional Knapsack with Family-Split Penalties
2021
Abstract The Multiple Multidimensional Knapsack Problem with Family-Split Penalties (MMdKFSP) is introduced as a new variant of both the more classical Multi-Knapsack and Multidimensional Knapsack Problems. It reckons with items categorized into families and where if an individual item is selected to maximize the profit, all the items of the same family must be selected as well. Items belonging to the same family can be assigned to different knapsacks; however, in this case, split penalties are incurred. This problem arises in resource management of distributed computing contexts and Service Oriented Architecture environments. An exact algorithm based on the exploitation of a specific combi…
A tabu search algorithm for large-scale guillotine (un)constrained two-dimensional cutting problems
2002
Abstract In this paper we develop several heuristic algorithms for the two-dimensional cutting problem (TDC) in which a single stock sheet has to be cut into a set of small pieces, while maximising the value of the pieces cut. They can be considered to be general purpose algorithms because they solve the four versions of the TDC: weighted and unweighted, constrained and unconstrained. We begin by proposing two constructive procedures based on simple bounds obtained by solving one-dimensional knapsack problems. We then use these constructive algorithms as building blocks for more complex procedures. We have developed a greedy randomised adaptive search procedure (GRASP) which is very fast an…
On Using a Hierarchy of Twofold Resource Allocation Automata to Solve Stochastic Nonlinear Resource Allocation Problems
2007
Recent trends in AI attempt to solve difficult NP-hard problems using intelligent techniques so as to obtain approximately-optimal solutions. In this paper, we consider a family of such problems which fall under the general umbrella of "knapsack-like" problems, and demonstrate how we can solve all of them fast and accurately using a hierarchy of Learning Automata (LA). In a multitude of real-world situations, resources must be allocated based on incomplete and noisy information, which often renders traditional resource allocation techniques ineffective. This paper addresses one such class of problems, namely, Stochastic Non-linear Fractional Knapsack Problems. We first present a completely …
Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems
2009
“Computational Intelligence” is an extremely wide-ranging and all-encompassing area. However, it is fair to say that the strength of a system that possesses “Computational Intelligence” can be quantified by its ability to solve problems that are intrinsically hard. One such class of NP-Hard problems concerns the so-called family of Knapsack Problems, and in this Chapter, we shall explain how a sub-field of Artificial Intelligence, namely that which involves “Learning Automata”, can be used to produce fast and accurate solutions to “difficult” and randomized versions of the Knapsack problem (KP).
Dynamic programming and Munkres algorithm for optimal photovoltaic arrays reconfiguration
2015
Abstract In this paper, an original formulation of the control problem for optimal PV array reconfiguration, following a Total Cross Tied layout, is proposed. The formulation follows the well-known subset sum problem, which is a special case of the knapsack problem. The reconfiguration is a measure devoted to mitigate the mismatch effect and maximize the output power of small photovoltaic plants under non-homogeneous working conditions. Therefore, reconfiguration means changing the connections of the solar panels adaptively by a dynamic switching matrix. The control system implements an easy dynamic programming algorithm to change the switches layout. The use of the Munkres assignment metho…