Search results for "NAPS"
showing 10 items of 302 documents
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…
Temporal coherency between receptor expression, neural activity and AP-1-dependent transcription regulates Drosophila motoneuron dendrite development.
2013
Neural activity has profound effects on the development of dendritic structure. Mechanisms that link neural activity to nuclear gene expression include activity-regulated factors, such as CREB, Crest or Mef2, as well as activity-regulated immediate-early genes, such as fos and jun. This study investigates the role of the transcriptional regulator AP-1, a Fos-Jun heterodimer, in activity-dependent dendritic structure development. We combine genetic manipulation, imaging and quantitative dendritic architecture analysis in a Drosophila single neuron model, the individually identified motoneuron MN5. First, Dα7 nicotinic acetylcholine receptors (nAChRs) and AP-1 are required for normal MN5 dend…
Cell Systems Bioelectricity: How Different Intercellular Gap Junctions Could Regionalize a Multicellular Aggregate
2021
Simple Summary Electric potential patterns across tissues are instructive for development, regeneration, and tumorigenesis because they can influence transcription, migration, and differentiation through biochemical and biomechanical downstream processes. Determining the origins of the spatial domains of distinct potential, which in turn decide anatomical features such as limbs, eyes, brain, and heart, is critical to a mature understanding of how bioelectric signaling drives morphogenesis. We studied theoretically how connexin proteins with different voltage-gated gap junction conductances can maintain multicellular regions at distinct membrane potentials. We analyzed a minimal model that i…
Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation
2013
Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The inter…
Evidence for an involvement of NMDA and non-NMDA receptors in synaptic excitation of phrenic motoneurons in the rabbit
1991
Abstract The action of endogenous excitatory amino acids on phrenic motoneurons was studied in anesthetized, vagotomized, paralyzed and artificially ventilated rabbits. The NMDA receptor antagonists APV and ketamine, as well as the non-NMDA receptor antagonists GAMS and DNQX were administered by microinjection into the ventral horn of the spinal segments C3-C5. Injection of each antagonist resulted in a reversible reduction of the phrenic nerve activity. Results suggest an important function of endogenous excitatory amino acids in the excitation of phrenic motneurons. NMDA as well as non-NMDA receptors are involved. The functional role of both receptor types in bulbospinal neurotransmission…