Search Results for "problem a"
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26 projects for "problem a" with 2 filters applied:
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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EasyCSP
Constraint Satisfaction Problem solving library for Java
EasyCSP is an open-source Java library for Constraint Satisfaction Programming. EasyCSP offers search algorithms for both CSPs and CSOPs. EasyCSP supports CSPs to be formalized using objects or int expressions. EasyCSP on GitHub: http://github.com/cordisvictor/easycsp-lib -
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scikit-opt
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing
...It includes genetic algorithms, particle swarm optimization, differential evolution, simulated annealing, ant colony optimization, immune algorithms, and artificial fish swarms. The package can address continuous objectives, constrained problems, and combinatorial tasks such as the traveling salesman problem. A consistent workflow lets users define an objective, configure an optimizer, run iterations, and inspect the best solution. Genetic algorithm operators can be replaced through user-defined functions or subclassing. Runs may continue from earlier iterations instead of restarting. Vectorization, threading, multiprocessing, caching, examples, and plotting support help users experiment with performance and convergence. -
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TSP Solver and Generator
Generate and solve Travelling Salesman Problem tasks
TSPSG is intended to generate and solve Travelling Salesman Problem (TSP) tasks. It uses Branch and Bound method for solving. An input is a number of cities and a matrix of city-to-city travel prices. The matrix can be populated with random values in a given range (useful for generating tasks). The result is an optimal route, its price, step-by-step matrices of solving and solving graph. The task can be saved in internal binary format and opened later. -
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Algorithms in Python
Data Structures and Algorithms in Python
Algorithms in Python is a collection of algorithm and data structure implementations (primarily in Python) meant to serve as both learning material and reference code for engineers. It includes code for graph algorithms, heap data structures, stacks, queues, and more — each implemented cleanly so learners can trace logic and adapt for their problems. The repository is particularly useful for people preparing for competitive programming, job interviews, or building a foundational... -
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Opt4J
Modular Java framework for meta-heuristic optimization
...It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary meta-heuristic optimization algorithms. For this purpose, Opt4J relies on a module-based implementation and offers a graphical user interface for the configuration as well as a visualization of the optimization process. -
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Primes
Calculate primes by using extremely fast sorting
This project considers the problem of calculating primes as a sorting problem. It includes the most efficient tree-based sorting algorithm that is possible and shows that finding a new prime can be done by sorting the differences between the previous primes in the right way. Unfortunately it has turned out that going this way is even more slowly than trying to find primes by brute force. -
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Bat2015
Bachelor of Science (Informatik)
The toolkit glpk supports methods for mixed integer linear programming (MILP). These methods solve Capital Budgeting Problems (CBP). Unfortunately, glpk does not support any multithreading and there is no feature to distribute problems via network connections. Today, this is a pitiable sight, because modern computer systems are coupled by networks and support multi threading. We create a distributed system with Apache thrift and the C-API of glpk. Now, it is possible to use as many cores in... -
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Diagonal
A command line toolki to solve a problem your favorite program defines
Diagonal can be used for: - getting descriptive statistics such as mean/median/mode with your program producing a sample - finding a root of an equation your program defines - calculating a fixed point of a function your program defines - detecting a cycle of a fuction your program defines as well as - decoding a VCDIFF file -
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The library for utilization of Minimal Quadtree format for storing very large sparse matrices. Please see the paper referenced below for the description of a problem. Corresponding papers: Tree-based Space Efficient Formats for Storing the Structure of Sparse Matrices (I. Šimeček, D. Langr, P. Tvrdík), In Scalable Computing: Practice and Experience, volume 15, 2014. Space Efficient Formats for Structure of Sparse Matrices Based on Tree Structures (I. Šimeček, Daniel Langr, Pavel Tvrdík), In Proceedings of 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC 2013), 2013. ...
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Approximate Subgraph Matching Algorithm
Approximate Subgraph Matching Algorithm for Dependency Graphs
The subgraph matching problem (subgraph isomorphism) is NP-complete. Previously, we designed an exact subgraph matching (ESM) algorithm for dependency graphs using a backtracking approach (http://esmalgorithm.sourceforge.net). We further designed an approximate subgraph matching (ASM) algorithm that is capable of detecting approximate subgraph matching based on a subgraph distance. -
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Water Retention on Magic Squares Solver
Water Retention on Magic Squares with Constraint-Based Local Search
A Constraint-Based Local Search solver for the Water Retention on Magic Squares-problem. The problem is a very hard combinatorial optimisation problem, invented by Craig Knecht. More can be read about it at: http://en.wikipedia.org/wiki/Water_retention_on_mathematical_surfaces Craig's website for the problem: http://www.knechtmagicsquare.paulscomputing.com/ The solver is mainly based on the theory and ideas from my bachelor thesis, which I wrote at Uppsala University, Sweden, for the Astra Group which does research about Constraint Programming and related technologies: Water Retention on Magic Squares with Constraint-Based Local Search http://urn.kb.se/resolve?... -
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Exact Subgraph Matching Algorithm
Exact Subgraph Matching Algorithm for Dependency Graphs
The subgraph matching problem (subgraph isomorphism) is NP-complete. We designed a simple exact subgraph matching (ESM) algorithm for dependency graphs using a backtracking approach. The total worst-case algorithm complexity is O(n^2 * k^n) where n is the number of vertices and k is the vertex degree. We have demonstrated the successful usage of our algorithm in three biomedical relation and event extraction applications: BioNLP 2011 shared tasks on event extraction, Protein-Residue association detection and Protein-Protein interaction identification. ... -
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...Current targets are GO board game and Texas Holdem poker. It investigates Genetic programming to build game AI logic. Also EA/GP simulations for TSP, Graph layout and Prisoners Dilemma problem.
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EGA
A novel and effictive GA algorithm to solve optimization problem
Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy. -
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Awakener aims to provide a Java library for solving practical, real world optimisation problems by means of genetic algorithms (turnkey algorithms for >= 90% of industry problems). Awakener extends Sleepwalker with specific algorithms.
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Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.
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Solution for UVa Online Judge's problem number 895 - Word Problem. This is the solution I uploaded, and it was accepted as valid.
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An implementation of LAYAGEN G(Diego-Mas 2010) for solves the layout planning problem using a simple genetic algorithm, and fully written in GAMBAS
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Kuhn-Munkres is used inside assignment problem solver application. Instance generator application creates input file for the solver. Checker application verifies the solution computed by the solver. A bash script compiles, executes these apps.
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Cycleopt optimizes the computational cost of multigrid algorithms. A cost and error model is used to optimally distribute the computational effort among the grids, depending on the desired accuracy of the solution and problem parameters.
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This project provides some hyperheuristics, implemented as C libraries. A hyperheuristic can be used to handle any optimization problem, as long as you implement some simple specific code to interact with it. Some examples/applications are also provided.
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FORce based Cluster Editing (FORCE) is a Java software heuristically solving the graph cluster editing problem on weighted edges using BLAST E-values. It further provides a training mode for heuristic parameter estimation.
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MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
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It moves by itself inside networks like virus infection & plagues, it is being written to solve computer virus problem drastically and responsibly. It is legal, free and open for public domain to improve W3 ICT Security.
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This projects implements various optimization heuristics and meta-heuristics (such as local search, VND, GRASP, Simulated Annealing, and more still to come) finding solutions on the post enrolment course timetabling problem.
