ACOTSPQAP is a software package that implements various Ant Colony Optimization algorithms for the symmetric travelling salesman problem (TSP) and the quadratic assignment problem (QAP). The ACO ...
Abstract: Conventional Ant Colony Optimization (ACO) exhibits slow convergence and high parameter sensitivity in unstructured continuous optimization. This paper proposes Gradient-Adaptive Step ACO ...
Abstract: The Traveling Salesman Problem (TSP) is a classic NP-hard optimization challenge where a salesman must find the shortest route visiting a series of locations exactly once before returning to ...
At first glance, the world of ants may seem far removed from our everyday lives. Yet, on closer inspection, they often face ...
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Master the art of simulation game building
Simulation games blend creativity, strategy, and systems thinking, letting players build worlds and solve complex challenges. From city planning to resource management, success comes from arranging ...
Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...
Ant societies rely on precise recognition systems to maintain cooperation, but new research reveals that these systems are more adaptable than once believed. For ants, quickly telling friend from foe ...
Deciphering cellular microenvironments at atlas scale remains challenging. Here, authors present a scalable contrastive learning framework using cell-centric subgraphs to map niches across platforms.
surabaya_map = mpimg.imread(".vscode\Optimization\Tugas_AI_Optimization\Lokasi_Kantor_Kecamatan_Surabaya.png") def show_Kecamatan(path, w=8, h=8): """Plot a TSP path overlaid on a map of the Kantor ...
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