Search results for " ANN"
showing 10 items of 1343 documents
Biased Modern Heuristics for the OCST Problem
2011
Biasing modern heuristics is an appropriate possibility in designing problem-specific and high-quality modern heuristics. If we have knowledge about a problem we can bias the design elements of modern heuristics, namely the representation and search operator, fitness function, the initial solution, or even the search strategy. This chapter presents a case study on how the performance of modern heuristics can be increased by biasing the design elements towards high-quality solutions. Results show that problem-specific and biased modern heuristics outperform standard variants and even for large problem instances high-quality solutions can be found.
Hydropower Optimization Using Split-Window, Meta-Heuristic and Genetic Algorithms
2019
In this paper, we try to find the most efficient optimization algorithm that can be used to resolve the hydropower optimization problem. We propose a novel optimization technique is called the Split-window method. The method is relatively simple and reduces the complexity of the optimization problem by split-ting the planning horizon (and datasets) into equal windows and assigning the same values to policies(actions) within each part. After splitting, a meta-heuristic technique is used to optimize the actions, and the dataset is split again until a split contains only one instance (timestep). The unique values to be optimized during each iteration is equal to the number of splits which make…
Developing Domain-Knowledge Evolutionary Algorithms for Network-on-Chip Application Mapping
2013
This paper addresses the Network-on-Chip (NoC) application mapping problem. This is an NP-hard problem that deals with the optimal topological placement of Intellectual Property cores onto the NoC tiles. Network-on-Chip application mapping Evolutionary Algorithms are developed, evaluated and optimized for minimizing the NoC communication energy. Two crossover and one mutation operators are proposed. It is analyzed how each optimization algorithm performs with every genetic operator, in terms of solution quality and convergence speed. Our proposed operators are compared with state-of-the-art genetic operators for permutation problems. Finally, the problem is approached in a multi-objective w…
GRASP and path relinking for the max–min diversity problem
2010
The max-min diversity problem (MMDP) consists in selecting a subset of elements from a given set in such a way that the diversity among the selected elements is maximized. The 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 the social and biological sciences. We propose a heuristic method-based on the GRASP and path relinking methodologies-for finding approximate solutions to this optimization problem. We explore different ways to hybridize GRASP and path relinking, including the recently proposed variant known as GRASP with evolutionary p…
A heuristic for fast convergence in interference-free channel assignment using D1EC coloring
2010
This work proposes an efficient method for solving the Distance-1 Edge Coloring problem (D1EC) for the assignment of orthogonal channels in wireless networks with changing topology. The coloring algorithm is performed by means of the simulated annealing method, a generalization of Monte Carlo methods for solving combinatorial problems. We show that the simulated annealing-based coloring converges fast to a suboptimal coloring scheme. Furthermore, a stateful implementation of the D1EC scheme is proposed, in which network coloring is executed upon topology changes. The stateful D1EC is also based on simulated annealing and reduces the algorithm’s convergence time by one order of magnitude in …
Parallel Simulated Annealing: Getting Super Linear Speedups
2005
The study described in this paper tries to improve and combine different approaches that are able to speed up applications of the Simulated Annealing model. It investigates separately two main aspects concerning the degree of parallelism an implementation can egectively exploit at the initial andfinal periods of an execution. As for case studies, it deals with two implementations: the Job shop Scheduling problem and the poryblio selection problem. The paper reports the results of a large number of experiments, carried out by means of a transputer network and a hypercube system. They give useful suggestions about selecting the most suitable values of the intervention parameters to achieve su…
Randomized heuristics for the Capacitated Clustering Problem
2017
In this paper, we investigate the adaptation of the Greedy Randomized Adaptive Search Procedure (GRASP) and Iterated Greedy methodologies to the Capacitated Clustering Problem (CCP). In particular, we focus on the effect of the balance between randomization and greediness on the performance of these multi-start heuristic search methods when solving this NP-hard problem. The former is a memory-less approach that constructs independent solutions, while the latter is a memory-based method that constructs linked solutions, obtained by partially rebuilding previous ones. Both are based on the combination of greediness and randomization in the constructive process, and coupled with a subsequent l…
Simulated Annealing in Bayesian Decision Theory
1992
Since the seminal paper by Kirkpatrick, Gelatt and Vechhi (1983), a number of papers in the scientific literature refer to simulated annealing as a powerful random optimization method which promises to deliver, within reasonable computing times, optimal or nearly optimal solutions to complex decision problems hitherto forbidding. The algorithm, which uses the physical process of annealing as a metaphor, is special in that, at each iteration, one may move with positive probability to solutions with higher values of the function to minimize, rather than directly jumping to the point with the smallest value within the neighborhood, thus drastically reducing the chances of getting trapped in lo…
Simulated annealing with restrained molecular dynamics using CONGEN: Energy refinement of the NMR solution structures of epidermal and type-αtransfor…
1996
The new functionality of the program CONGEN (Bruccoleri RE, Karplus M, 1987, Biopolymers 26:137-168; Bassolino-Klimas D et al., 1996, Protein Sci 5:593-603) has been applied for energy refinement of two previously determined solution NMR structures, murine epidermal growth factor (mEGF) and human type-alpha transforming growth factor (hTGF alpha). A summary of considerations used in converting experimental NMR data into distance constraints for CONGEN is presented. A general protocol for simulated annealing with restrained molecular dynamics is applied to generate NMR solution structures using CONGEN together with real experimental NMR data. A total of 730 NMR-derived constraints for mEGF a…
A Simple Analytical Model for Remote Assessment of the Dynamics of Biomass Accumulation
2011
Efficient means for assessment of the dynamics and the state of the stocks of renewable assets such as wood biomass are important for sustainable supplies satisfying current needs. So far attention has been paid mainly to the economic aspects of forest management while ecological problems are rising with the expected transfer from fossil to renewable resources supplies of which from forest being essential for traditional consumers of wood and for emerging biorefineries. Production of biomass is more reliant on assets other than money the land (territory) available and suitable for the purpose being the first in the number. Studies of the ecological impacts (the “footprint”) of sustainable u…