Aug 6, 2018 · Local optima networks for both iterated local search and a hybrid genetic algorithm, across different neighbourhoods, are compared, highlighting the differences in how the landscape is explored. The search landscape is a common metaphor to describe the structure of computational search spaces.

The paper introduces an AND/OR search space perspective for graphical models that include probabilistic networks (directed or undirected) and constraint networks. In contrast to the traditional (OR) search space view, the AND/OR search tree displays

Aug 22, 2024 · Local search algorithms are essential tools in artificial intelligence and optimization, employed to find high-quality solutions in large and complex problem spaces. Key algorithms include Hill-Climbing Search, Simulated Annealing, Local Beam Search, Genetic Algorithms, and Tabu Search.

The visualization shows the search landscape as seen by the search algorithm. It supports the topological analysis as well as the comparison of search landscapes. We showcase the method by applying it to two different search operators on the TSP, the QAP, and the SMTTP.

In this paper we present and discuss a set of techniques for the visualization of search landscapes aimed at supporting the researcher’s intuition on the behavior of a Stochastic Local Search algorithm applied to a combinatorial optimization problem.

Jun 3, 2017 · We propose a visualization system that gives a visual intuition about topological properties of the search landscape. We obtain representative samples of the search landscape and its optima by random sampling and by computing the related optima using local search.

Jun 25, 2005 · We give a new interpretation to the concept of "landscape". This allows us to develop a new theoretical model to study search algorithms. Particularly, we are able to quantify the amount and...

Jan 15, 2012 · Scientific visualization of geospatial data provides highly effective tools for analysis and communication of information about the land surface and its features, properties, and temporal evolution.

Apr 29, 2025 · Large Language Models (LLMs) have demonstrated significant potential in algorithm design. However, when integrated into search frameworks for iterative algorithm search, the underlying fitness landscape--critical for understanding search behaviou--remains underexplored. In this paper, we illustrate and analyze the fitness landscape of LLM-assisted Algorithm Search (LAS) using a graph-based ...

Apr 22, 2024 · Examples of local search algorithms include hill climbing, simulated annealing, and genetic algorithms. They are commonly used in various fields such as operations research, artificial intelligence, and computer science for solving problems like scheduling, routing, and resource allocation. 1. Hill Climbing Algorithm. 2. Genetic Algorithm.