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This paper addresses the problem of optimizing a Demand Responsive Transport (DRT) service. A DRT is a flexible transportation service that provides on-demand transport for users who formulate requests specifying desired locations and times of pick-up ...
This work presents interesting multi-point search algorithms exploiting several surrogate models, implemented in MI-NAMO, the multi-disciplinary optimization platform of Cenaero. Many types of surrogate models are used in the literature with their own ...
Insights on characteristics of an optimization problem is highly important in order to select and configure the right algorithm. Some techniques called features are defined for analyzing the fitness landscape of a problem. Despite their successes, our ...
Previous work presented a technique called evolving self-taught neural networks - neural networks that can teach themselves, intrinsically motivated, without external supervision or reward [3]. In an autonomous multi-agent setting in which the agent is ...
The performance comparison of multi-objective evolutionary algorithms (MOEAs) has been a broadly studied research area. For almost two decades, quality indicators (QIs) have been employed to quantitatively compare the Pareto front approximations ...
This paper proposes a new discrete optimization benchmark 100b-Digit, a binary discretized version for the 100-Digit Challenge. The continuous version 100-Digit Challenge utilizing continuous input parameters for a fitness function was suggested for the ...
The primary focus of the machine learning model is to train a system to achieve self-reliance. However, due to the absence of the inbuilt security functions the learning phase itself is not secured which allows attacker to exploit the security ...
One of the main goals of the COCO platform is to produce, collect, and make available benchmarking performance data sets of optimization algorithms and, more concretely, algorithm implementations. For the recently proposed biobjective bbob-biobj test ...
Uniform Random Search is considered the simplest of all randomized search strategies and thus a natural baseline in benchmarking. Yet, in continuous domain it has its search domain width as a parameter that potentially has a strong effect on its ...
In this paper we benchmark five variants of CMA-ES for optimization in large dimension on the novel large scale testbed of COCO under default or modified parameter settings. In particular, we compare the performance of the separable CMA-ES, of VD-CMA-ES ...
In this paper, we propose a comparative benchmark of MO-CMA-ES, COMO-CMA-ES (recently introduced in [12]) and NSGA-II, using the COCO framework for performance assessment and the Bi-objective test suite bbob-biobj. For a fixed number of points p, COMO-...
In this article we benchmark eight multivariate local solvers as well as the global Differential Evolution algorithm from the Python SciPy library on the BBOB noiseless testbed. We experiment with different parameter settings and termination conditions ...
A typical scenario when solving industrial single or multiobjective optimization problems is that no explicit formulation of the problem is available. Instead, a dataset containing vectors of decision variables together with their objective function ...
The most commonly used statistics in Evolutionary Computation (EC) are of the Wilcoxon-Mann-Whitney-test type, in its either paired or non-paired version. However, using such statistics for drawing performance comparisons has several known drawbacks. At ...
In our proposed method, an object can be detected from time-series images taken by two or a few cameras. When one of the cameras detects that the object has moved, a system locates that object from the images taken by the other camera(s) by using the ...
Caregivers in nursing facilities are too busy to pay attention constantly to care receivers. Recently, some cameras have been set up in some nursing facilities. However, the caregivers cannot continuously monitor the care receivers on a display in the ...
In this paper, four systems for disaster countermeasures were implemented. The first one was a 3D reconstruction system. It would construct a 3D model from images taken by a drone. The second one was a human detection and posture analyzing system. A ...
When a big disaster occurs, a rescue team has to send the food and/or supplies to an unspecified number of affected people. Therefore, an evolutionary method that can provide service to unspecific large number of users is needed. In this paper, an ...
In this paper we propose the use of Minimum Spanning Tree-based clustering to recursively cluster large sets of potentially Pareto-optimal solutions. We present preliminary results for the multiobjective traveling salesperson problem. The clustering is ...
1Since Internet addiction (IA) was reported in 1996, research on IA assessment has attracted considerable interest. The development of a real-time detector system can help communities, educational institutes, or clinics immediately assess the risk of IA ...