Genetic Algorithm for the 0/1 Multidimensional Knapsack Problem
원문 초록
The 0/1 multidimensional knapsack problem is the 0/1 knapsack problem with m constraints which makes it difficult to solve using traditional methods like dynamic programming or branch and bound algorithms. We present a genetic algorithm for the multidimensional knapsack problem with Java and C++ code that is able to solve publicly available instances in a very short computational duration. Our algorithm uses iteratively computed Lagrangian multipliers as constraint weights to augment the greedy algorithm for the multidimensional knapsack problem and uses that information in a greedy crossover in a genetic algorithm. The algorithm uses several other hyperparameters which can be set in the code to control convergence. Our algorithm improves upon the algorithm by Chu and Beasley in that it converges to optimum or near optimum solutions much faster.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Program Semantic Inequivalence Game with Large Language Models
GPRat: Gaussian Process Regression with Asynchronous Tasks
EIQP: Execution-time-certified and Infeasibility-detecting QP Solver
C codegen considered unnecessary: go directly to binary, do not pass C. Compilation of Julia code for deployment in model-based engineering
Fortran2CPP: Automating Fortran-to-C++ Translation using LLMs via Multi-Turn Dialogue and Dual-Agent Integration
SceneGenAgent: Precise Industrial Scene Generation with Coding Agent
토론
이 논문과 연결된 포럼 글이 아직 없습니다.