Search Results for "problem a"
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Showing 39 open source projects for "problem a"
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Digraph3
A collection of python3 modules for Algorithmic Decision Theory
...Technical documentation and tutorials are available under the following link: https://digraph3.readthedocs.io/en/latest/ The tutorials introduce the main objects like digraphs, outranking digraphs and performance tableaux. There is also a tutorial provided on undirected graphs. Some tutorials are problem oriented and show how to compute the winner of an election, how to build a best choice recommendation, or how to linearly rank or rate with multiple incommensurable performance criteria. Other tutorials concern more specifically operational aspects of computing maximal independent sets (MISs) and kernels in graphs and digraphs. -
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Continuation Core and Toolboxes (COCO)
Toolboxes for parameter continuation and bifurcation analysis.
Development platform and toolboxes for parameter continuation, e.g., bifurcation analysis of dynamical systems and constrained design optimization. This material is based upon work partially supported by the National Science Foundation under Grant No. 1016467 and the Danish research council (FTP) under the project number 0602-00753B. Any opinions, findings, and conclusions or recommendations expressed on this site are those of the authors and do not necessarily reflect the views of the... -
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HungarianAlgorithm
An Ada implementation of the Hungarian Algorithm to minimize cost
The Hungarian algorithm can be described as optimally solving a workers versus jobs assignment problem that minimizes total cost. This implementation assumes a square cost matrix, i.e. the number of jobs equals the number of workers to do them. -
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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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VS Code LeetCode
Solve LeetCode problems in VS Code
...The accounts of different endpoints are not shared. Please make sure you are using the right endpoint. The extension will use leetcode.com by default. Directly click on the problem or right-click the problem in the LeetCode Explorer and select Preview Problem to see the problem description. Select Show Problem to directly open the file with the problem description. The extension supports 5 editor shortcuts (aka Code Lens). To manage your LeetCode sessions, just clicking the LeetCode: *** at the bottom of the status bar. ... -
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LeetCode Python
LeetCode Solutions: A Record of My Problem Solving Journey
This repository is a comprehensive personal journal of LeetCode problem-solving journey. It includes detailed solutions with code, algorithm insights, data structure summaries, Anki flashcards, daily challenge logs, and future planning sections. -
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Data Structures and Algorithms in JS
Data Structures and Algorithms explained and implemented in JavaScript
...Improve your problem-solving skills and become a stronger developer by understanding fundamental computer science concepts. -
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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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interactive-coding-challenges
120+ interactive Python coding interview challenges
Interactive Coding Challenges is a collection of practice problems designed to strengthen data structures, algorithms, and problem-solving skills. The repository emphasizes a learn-by-doing approach: you read a prompt, attempt a solution, and verify behavior with tests, often within notebooks or scripts. Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference solutions so you can compare approaches and learn idiomatic patterns. ... -
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frontend-interview
The strongest front-end interview guide in the universe
This is a review summary project about preparing for front-end interviews that I have summarized, and the project is updated from time to time. This is not only a strategy for job interviews, but also a collection of front-end ers to examine themselves and achieve breakthroughs. I hope that through this guide, everyone can open up their own lines of Ren and Du, and go further on the road to the front. This warehouse uses a large number of diagrams to convey knowledge. The so-called picture... -
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FuzzyWuzzy
Fuzzy string matching in Python
We’ve made it our mission to pull in event tickets from every corner of the internet, showing you them all on the same screen so you can compare them and get to your game/concert/show as quickly as possible. Of course, a big problem with most corners of the internet is labeling. One of our most consistently frustrating issues is trying to figure out whether two ticket listings are for the same real-life event (that is, without enlisting the help of our army of interns). To pick an example completely at random, Cirque du Soleil has a show running in New York called “Zarkana”. ... -
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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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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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The project objective is the development of an optimization algorithm for the problem of stowing general cargo into platform supply vessels.
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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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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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FJSP Software
A Software for Flexible Job Shop Scheduling
Flexible job shop scheduling problem (FJSP) is very important in many fields such as production management, resource allocation and combinatorial optimization. In the real manufacturing systems, each operation could be processed on more than one machine and each machine can also process several operations. This feature is known as flexibility. You can define your problem in this software and get an optimal solution as a Gantt Chart. -
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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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Asteroid
A CBLS Engine in SCALA, NOW part of OscaR
...Follow us on https://bitbucket.org/oscarlib/oscar/wiki/Home Asteroid offers a powerful framework for developing constraint-based local search solution to combinatorial problems. This technique provides good scalability to real-world problems. It includes a library of standard constraints and invariants to declaratively define the problem you want to solve, and it also provides powerful search mechanisms. -
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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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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.
