Search results for "Heuristic"

HEURISTIC ALGORITHMS FOR RESOURCE-CONSTRAINED PROJECT SCHEDULING: A REVIEW AND AN EMPIRICAL ANALYSIS

1989

Detection of local tourism systems by threshold accepting

2015

Despite the importance of tourism as a leading industry in the development of a country’s economy, there is a lack of criteria and methodologies for the detection, promotion, and governance of local tourism systems. We propose a quantitative approach for the detection of local tourism systems the size of which is optimal with respect to geographical, economic, and demographical criteria: we formulate the problem as an optimisation problem and we solve it by a metaheuristic approach; then we compare the obtained results with standard clustering approaches and with an exact optimisation solver. Results show that our approach requires low computational times to provide results that are better …

An original multi-objective criterion for the design of small-scale polygeneration systems based on realistic operating conditions

2008

The optimal design and operation of cogeneration and trigeneration systems for buildings applications is a complex issue, which has been investigated by several different approaches. Both the two basic management strategies, namely heat-tracking and electricity-tracking, have advantages and drawbacks in terms of operating results and may lead the plant designer either to undersize or oversize the CHP unit with respect to the optimal lay-out. Experimental works have demonstrated how the actual on-site performance of small-scale polygeneration systems significantly differs from their expected operation, due to the need for a regular plant operation and the effects of outages for scheduled or …

Combined Elephant Herding Optimization Algorithm with K-means for Data Clustering

2018

Clustering is an important task in machine learning and data mining. Due to various applications that use clustering, numerous clustering methods were proposed. One well-known, simple, and widely used clustering algorithm is k-means. The main problem of this algorithm is its tendency of getting trapped into local minimum because it does not have any kind of global search. Clustering is a hard optimization problem, and swarm intelligence stochastic optimization algorithms are proved to be successful for such tasks. In this paper, we propose recent swarm intelligence elephant herding optimization algorithm for data clustering. Local search of the elephant herding optimization algorithm was im…

Heuristics for solving the parameter tuning problem in motion cueing algorithms.

2017

[ES] Diversos tipos de plataformas robóticas son empleadas habitualmente para la generación de claves gravito-inerciales en simuladores. Además del control de los actuadores, dichas plataformas deben ejecutar complejos algoritmos de control conocidos como algoritmos de washout, que deben ser ajustados para que el movimiento generado sea similar al simulado. El ajuste de dichos algoritmos es complejo por el elevado número de parámetros que poseen. Además, dicho ajuste se ha venido realizando tradicionalmente de modo manual mediante evaluaciones subjetivas. En este trabajo, los autores proponen un método automático de ajuste basado en optimización heurística, métricas objetivas, y simulación …

Greedy and K-Greedy algoritmhs for multidimensional data association

2011

[EN] The multidimensional assignment (MDA) problem is a combinatorial optimization problem arising in many applications, for instance multitarget tracking (MTT). The objective of an MDA problem of dimension $d\in\Bbb{N}$ is to match groups of $d$ objects in such a way that each measurement is associated with at most one track and each track is associated with at most one measurement from each list, optimizing a certain objective function. It is well known that the MDA problem is NP-hard for $d\geq3$. In this paper five new polynomial time heuristics to solve the MDA problem arising in MTT are presented. They are all based on the semi-greedy approach introduced in earlier research. Experimen…

Optimization of Data Harvesters Deployment in an Urban Areas for an Emergency Scenario

2013

International audience; Since its appearance in the VANETs research community, data collection where vehicles have to explore an area and collect various local data, brings various issues and challenges. Some architectures were proposed to meet data collection requirements. They can be classified into two categories: Decentralized and Centralized self-organizing where different components and techniques are used depending on the application type. In this paper, we treat time-constrained applications in the context of search and rescue missions. For this reason, we propose a centralized architecture where a central unit plans and manages a set of vehicles namely harvesters to get a clear ove…

An enhanced memetic differential evolution in filter design for defect detection in paper production.

2008

This article proposes an Enhanced Memetic Differential Evolution (EMDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. Defect detection is handled by means of two Gabor filters and their design is performed by the EMDE. The EMDE is a novel adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution with the exploitative features of three local search algorithms employing different pivot rules and neighborhood generating functions. These local search algorithms are the Hooke Jeeves Algorithm, a Stochastic Local Search, and Simulated Annealing. The local search algorithms are adap…

A parallel simulated annealing approach to the K shortest loopless paths problem

1997

The k shortest loopless paths problem is a significant combinatorial problem which arises in many contexts. When the size of the networks is very large the exact algorithms fail to find the best solution in a reasonable time. The aim of this paper is to suggest parallel efficient algorithms to obtain a good approximation of the solution to the k shortest loopless paths problem between two arbitrary nodes, when the network size is large. The heuristic used is known in literature as Simulated Annealing. Preliminary tests have been conducted for evaluating the validity of the proposed algorithms. The quality of the obtained results represents a significant base for further experimentations.

Minimizing weighted earliness-tardiness on parallel machines using hybrid metaheuristics

2015

We consider the problem of scheduling a set of jobs on a set of identical parallel machines where the objective is to minimize the total weighted earliness and tardiness penalties with respect to a common due date. We propose a hybrid heuristic algorithm for constructing good solutions, combining priority rules for assigning jobs to machines and a local search with exact procedures for solving the one-machine subproblems. These solutions are then used in two metaheuristic frameworks, Path Relinking and Scatter Search, to obtain high quality solutions for the problem. The algorithms are tested on a large number of test instances to assess the efficiency of the proposed strategies. The result…