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Opis: Observing the developments and intersections between music, graphics, video, code and club culture in the music scene around the year 2010, primarily based in England, a new cultural movement known as ”Algorave” has emerged, reshaping the boundaries of new artistic expression. While the practices of live and creative coding had been present on the global stage for some time, the “Algorave” scene emerges as a unique blend of these artistic directions, combining various elements and offering a distinctive sound-visual artistic expression. Unlike traditional music performances, artists of this movement openly share their live coding processes with the audience, guiding them through the entire process of the performance. By utilizing live coding as the primary artistic tool and integrating it with artificial intelligence, the work Dreamer demonstrates a fusion of these two approaches. It visually explores dreams using images generated by AI technology. These images are then manipulated through live coding techniques, creating a visual narrative that is accompanied by ambient-electronic sounds. The sound complements the visual elements, achieved through the use of various synthesizers, samplings and granular synthesis, a technique that fragments sound into small grains to create complex sound textures. Beyond its practical execution, Dreamer addresses dreams as something unknown and undisclosed. It raises the question of whether dreams can be considered insights into our parallel lives, or are they merely products of our imagination? Should we explore them rather than just observe them? Based on these questions, the work examines dreams through programming and technology, seeking new possibilities for artistic expression.
Ključne besede: code, sound, algorithm, visual art, algorave, technology, master's thesis
Objavljeno v RUNG: 03.10.2024; Ogledov: 1363; Prenosov: 9
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Opis: In this article, an improved harmony search algorithm (IHSA) that utilizes opposition-based learning is presented for solving the maximal covering location problem (MCLP). The MCLP is a well-known facility location problem where a fixed number of facilities are opened at a given potential set of facility locations such that the sum of the demands of customers covered by the open facilities is maximized. Here, the performance of the harmony search algorithm (HSA) is improved by incorporating opposition-based learning that utilizes opposite, quasi-opposite and quasi-reflected numbers. Moreover, a local search heuristic is used to improve the performance of the HSA further. The proposed IHSA is employed to solve 83 real-world MCLP instances. The performance of the IHSA is compared with a Lagrangean/surrogate relaxation-based heuristic, a customized genetic algorithm with local refinement, and an improved chemical reaction optimization-based algorithm. The proposed IHSA is found to perform well in solving the MCLP instances.
Ključne besede: maximal covering location problem, harmony search algorithm, opposition-based learning, facility location problem, opposite number
Objavljeno v RUNG: 05.10.2023; Ogledov: 2932; Prenosov: 13
Celotno besedilo (2,69 MB)
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Opis: It is often needed to install limited number of facilities to address the demand of customers due to resource constraints and thus the requirement to provide service to all customers is not possible to meet. In such situation, the facilities are installed (placed) so that the maximum demand can be met. The problem of installing (locating) such facilities are known as Maximal Covering Location Problem (MCLP) [2] in facility location [1]. We assume that (i) all facilities are in a plane, and (ii) all customers can be considered as a point set on the same plane. The type of covering area (or range) of a facility depends on the facility to be installed. We consider the MCLP where the covering area (or range) of each facility is the area of a square with fixed size. In other words here, each facility is installed at the center of the square. The problem considered in this article is defined as follows: given a set P of n input points (customers) on the plane and k squares (facilities) each of fixed size, the objective is to find a placement of k squares so that the union of k axis parallel squares covers (contains) the maximum numbers of input points where k (1≤k≤n) is a positive integer constant. This problem is known to be NP-hard [5]. We have proposed a genetic algorithm (GA) to solve this problem.
Ključne besede: Maximal Covering Location Problem, Facility Location, Genetic Algorithm
Objavljeno v RUNG: 05.06.2023; Ogledov: 2461; Prenosov: 0
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Opis: Given a set P of n-points (customers) on the plane and a positive integer k (1 ≤ k ≤ n), the objective is to find a placement of k circles (facilities) such that the union of k circles contains all the points of P and the sum of the radii of the circles is minimized. We have proposed a Genetic Algorithm (GA) to solve this problem. In this context, we have also proposed two different algorithms for k=1 and 2. Finally, we have proposed a GA to solve another optimization problem to compute a placement of fixed number of facilities where the facilities are hazardous in nature and the range of each such facility is circular.
Ključne besede: Facility Location, Enclosing Problem, Optimization Problem, Genetic Algorithm
Objavljeno v RUNG: 05.06.2023; Ogledov: 2238; Prenosov: 0
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Opis: The tool indexing problem (TIP) is the problem of allocating cutting tools to different slots in a tool magazine of Computer Numerically Controlled machine to reduce the processing time of jobs on the machine. This is one of the mostly encountered optimization problems in manufacturing systems. In TIP, the number of tools used by the machine is at most the number of slots available in the tool magazine. In this article, a customized harmony search (HS) algorithm, which utilizes a harmony refinement strategy for faster convergence, is presented to solve TIP. The harmony refinement method also helps to avoid getting stuck into local optima. The performance of the proposed method is tested on 27 instances taken from the literature and out of these it is found to improve the best known solutions for 16 instances. For the remaining instances, it gives the same results as found in the literature. Moreover, the performance of the proposed algorithm is tested on newly adapted 41 instances and for some of these instances the results obtained using the proposed algorithm are compared with that obtained using CPLEX.
Ključne besede: Tool indexing problem (TIP), Computer Numerically Controlled (CNC) machine, Harmony search (HS) algorithm, Automatic tool changer (ATC), CPLEX
Objavljeno v RUNG: 17.04.2023; Ogledov: 3125; Prenosov: 0
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