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Recently, Radon transformation has been used to generate barcodes for tagging medical images. The under-sampled image is projected in certain directions, and each projection is binarized using a local threshold. The concatenation of the thresholded projections creates a barcode that can be used for tagging or annotating medical images. A small number of equidistant projections, e.g., 4 or 8, is generally...
The study of proteins and the prediction of their three-dimensional (3-D) structure is one of the most challenging problems in Structural Bioinformatics. Over the last years, several computational strategies have been proposed as a solution to this problem. As revealed by recent CASP experiments, the best results have been achieved by knowledge-based methods. Despite the advances in the development...
Differential Evolution (DE) has been successfully applied to various optimization problems. The performance of DE is affected by algorithm parameters such as a scaling factor F and a crossover rate CR. Many studies have been done to control the parameters adaptively. One of the most successful studies on parameter control is JADE. In JADE, the two parameter values are generated according to two probability...
In the modern manufacturing and operations management, on-time delivery is a critical factor towards realizing customer satisfaction. This paper focuses on job-shop scheduling problem to minimize total weighted tardiness and proposes a discrete differential evolution algorithm for this problem. In order to improve the search ability and efficiency, this paper hybrids the local search which is based...
Differential evolution (DE) is a high performance and easy to implement evolutionary algorithm. The DE algorithm with small population size (i.e., micro-DE) can further increase the efficiency of the algorithm. However, it also decreases its exploration capability, causing stagnation and pre-mature convergence. In this paper, the idea of exploration enhancement at the mutation level is proposed. The...
Opposition-based learning (OBL) is a recently proposed method, which is successfully used to accelerate the search process of some well-known techniques in soft computing, such as swarm and evolutionary algorithms, artificial neural networks, reinforcement learning, and fuzzy logic systems. Among these opposition-based algorithms, opposition-based differential evolution (ODE) is one of the most popular...
Differential Evolution (DE), a population-based stochastic search technique is adept at solving real-world optimization problems. Unlike most population based algorithms, the use of DE is usually inexpedient in solving expensive optimization problems as the computational costs of these simulations are excessively high. This problem can be resolved by commingling surrogate model in DE that approximates...
This paper proposes a new evolutionary algorithm (EA), which is called the natural aggregation algorithm (NAA). NAA is inspired by the collective decision making intelligence of the group-living animals. Distinguished from other EAs, NAA distributes individuals to several sub-populations (called ‘shelters’), and uses a stochastic migration model to dynamically mitigate the individuals among the shelters...
Memetic algorithms, which hybridise evolutionary algorithms with local search, are well-known metaheuristics for solving combinatorial optimisation problems. A common issue with the application of a memetic algorithm is determining the best initial setting for the algorithmic parameters, but these can greatly influence its overall performance. Unlike traditional studies where parameters are tuned...
In this paper, it is experimentally verified that TDGA (Thermo Dynamical Genetic Algorithm) is effective in solving a function optimization problem using Genetic Algorithms, because of its sustainability of population diversity and efficiency of searching for solutions. We experimentally and quantitatively verify the hypothesis that we can improve the ratio of searching for the optimum solution and...
The rearrangement of genomes is an important tool for studying the evolution of genomes and specifically for the construction of phylogenies. A translocation splits and combines the strings of genes of a pair of chromosomes inside a genome and is considered a suitable operation for rearrangement of genomes with multiple chromosomes. The translocation distance between two genomes is the minimum number...
The classification performance of a weighted voting ensemble of classifiers largely depends on the proper weight chosen for each base classifier's vote. In this paper, we propose the use of Differential Evolution algorithm for adjustment of voting-weights of base classifiers used in a heterogeneous ensemble of classifiers (HEoC). We used the average Matthews Correlation Coefficient (MCC), calculated...
Load Patterns (LPs) clustering has a broad range of applications, such as tariff formulation, power system planning, load forecasting, and so on. In this paper, we develop a multi-objective version of Differential Evolution (DE) using a Pareto Tournament (PT) selection to solve the LP clustering problem. Our automatic DE LP clustering (ADE-LPC) algorithm provides an entire Pareto front, and by incorporating...
A polyomino puzzle is a collection of polyominos that can be joined to make a simple shape. The game Ten-Yen was one of the first of these. It has ten polyomino pieces that could be used to make a 6×6 square in a variety of ways. In this study we define representations and fitness functions for generating polyomino puzzles as well as developing a simple solver to compare the evolved puzzles. The solver...
Divide the dollar is a two-player simultaneous derived from a game invented by John Nash because its strategy space has an entire subspace of Nash equilibria. This study describes and explores a family of generalizations of divide the dollar with easily controlled properties. If we view divide the dollar as modeling the process of making a bargain, then the generalized game makes it easy to model...
Spatial games are extensively used to study how cooperation evolves in human populations. Nevertheless, spatial games have several limitations which can produce misleading results. Specifically, the regular lattice structure creates artificial interactions and the reliance on a Moran process updating, coupled with weak selection, makes it difficult to switch strategies. These problems contribute to...
The iterated prisoner's dilemma is a simultaneous two-player game widely used in studies on cooperation and conflict. Past work has shown that the choice of representation or available resources such as the number of states or neurons of evolving agents has a large impact on the behavior of evolved agents. This study revisits three qualities of the agent training algorithm for finite state agents...
Design of multi-component structures can be a challenging task. While having multiple components in a complex structure is often necessary in order to reduce the manufacturing cost, multiple components need joining operations. Optimal design of joints is not a decoupled problem from designing the base structure, and often comes at balancing trade-offs in assembly cost, weight and structural performance...
Urban planners face increasing challenges to design and optimize sustainable cities. Evolutionary algorithms are an important tool for design optimization and can help urban planners finding alternative optimal designs to increase the sustainability of cities. Mobility and transportation are two important components of modern cities that are amenable to simulation and their design can be improved...
Methods aiming detection and inference of spatial clusters are of great relevance. Both for its applicability to public health problems, as well as for the effective scientific interest in the development of these methods. The main techniques are based on spatial scan statistics and many applications link this statistic in efficient optimization methods. Recently, regularity functions have been proposed...
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