Search Results - branch and bound knapsack problems multiobjective (evolutionary OR evolution) algorithms

Solving multiobjective, multiconstraint knapsack problems using mathematical programming and evolutionary algorithms

Authors: Florios, Kostas Mavrotas, George Diakoulaki, Danae

Source: European Journal of Operational Research. May2010, Vol. 203 Issue 1, p14-21. 8p.

Subject Terms: *ALGORITHMS, *MATHEMATICAL programming, *HEURISTIC, *OPERATIONS research, KNAPSACK problems, EVOLUTIONARY computation, BRANCH & bound algorithms, METRIC system

Improvement of genetic algorithms with decomposition procedures for large-scale multiobjective multidimensional 0-1 knapsack problems incorporating fuzzy goals.

Authors: Kato, Kosuke Sakawa, Masatoshi Ikegame, Toshinori

Source: Electronics & Communications in Japan, Part 3: Fundamental Electronic Science; Dec2000, Vol. 83 Issue 12, p62-69, 8p

Subject Terms: KNAPSACK problems, INTEGER programming, BRANCH & bound algorithms, MATHEMATICAL programming, GENETIC algorithms

Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approach.

Authors: Zitzler, Eckart Thiele, Lothar

Source: IEEE Transactions on Evolutionary Computation; Nov1999, Vol. 3 Issue 4, p257, 15p

Subject Terms: ALGORITHMS, KNAPSACK problems, CLUSTER analysis (Statistics), SYSTEMS software, MATHEMATICAL optimization

A Multi-Constrained Knapsack Approach for Educational Resource Allocation: Genetic Algorithm with Category- Specific Optimization.

Authors: Tsamis, George Vassiliou, Giannis Chatzinikolaou, Stavroula et al.

Source: Electronics (2079-9292); Oct2025, Vol. 14 Issue 19, p3898, 32p

Subject Terms: EDUCATIONAL resources, RESOURCE allocation, FEASIBILITY studies, SCHOLARLY method, GENETIC algorithms, METAHEURISTIC algorithms, DECISION support systems, KNAPSACK problems

Binary Mountain Gazelle Optimizer and Binary Enhanced Mountain Gazelle Optimizer for 0–1 knapsack problems and uncapacitated facilty location problems.

Authors: Bas, Emine Ihsan, Aysegul

Source: Evolving Systems; Dec2025, Vol. 16 Issue 4, p1-69, 69p

A Heuristics-Guided Simplified Discrete Harmony Search Algorithm for Solving 0-1 Knapsack Problem.

Authors: Zheng, Fuyuan Cheng, Kanglong Yang, Kai et al.

Source: Algorithms; May2025, Vol. 18 Issue 5, p295, 31p

Subject Terms: SEARCH algorithms, RANDOM operators, KNAPSACK problems, ALGORITHMS, BACKPACKS, HEURISTIC

Enhanced Particle Swarm Optimization for Dual-Constraint Multi-Knapsack Problems: A Real-World Retail Packaging Application.

Authors: Rizqa, Ifan Syukur, Abdul Rijati, Nova et al.

Source: Journal Européen des Systèmes Automatisés; Aug2025, Vol. 58 Issue 8, p1745-1756, 12p

Subject Terms: PARTICLE swarm optimization, KNAPSACK problems, PACKAGING design, RETAIL industry, RESOURCE allocation, CONSTRAINT programming, EMPIRICAL research, METAHEURISTIC algorithms

Parallel implementation of an exact two-phase method for the biobjective knapsack problem.

Authors: Chaabane, Khadidja Bouroubi, Sadek Djellouli, Younes

Source: RAIRO: Operations Research (2804-7303); 2024, Vol. 58 Issue 4, p3347-3367, 21p

Subject Terms: COMBINATORIAL optimization, PARALLEL programming, TEST methods, ALGORITHMS, KNAPSACK problems, LITERATURE

TMHSCA: a novel hybrid two-stage mutation with a sine cosine algorithm for discounted {0-1} knapsack problems.

Authors: Kang, Yan Wang, Haining Pu, Bin et al.

Source: Neural Computing & Applications; Jun2023, Vol. 35 Issue 17, p12691-12713, 23p

Subject Terms: KNAPSACK problems, GREEDY algorithms, DIFFERENTIAL operators, ALGORITHMS, METAHEURISTIC algorithms, DIFFERENTIAL evolution, NP-hard problems

An efficient binary spider wasp optimizer for multi-dimensional knapsack instances: experimental validation and analysis.

Authors: Abdel-Basset, Mohamed Mohamed, Reda Sallam, Karam M. et al.

Source: Journal of Big Data; 1/28/2025, Vol. 12 Issue 1, p1-56, 56p

Subject Terms: GENETIC algorithms, NP-hard problems, TRANSFER functions, RESEARCH personnel, WASPS, KNAPSACK problems

Reinforcement Learning for Solving the Knapsack Problem.

Authors: Zhang, Zhenfu Yin, Haiyan Zuo, Liudong et al.

Source: Computers, Materials & Continua; 2025, Vol. 84 Issue 1, p919-936, 18p

Subject Terms: REINFORCEMENT learning, TIME complexity, DYNAMIC programming, COMBINATORIAL optimization, PROBLEM solving, KNAPSACK problems

Set Theory-Based Operator Design in Evolutionary Algorithms for Solving Knapsack Problems.

Authors: Wang, Ran Zhang, Zichao

Source: IEEE Transactions on Evolutionary Computation; Dec2021, Vol. 25 Issue 6, p1133-1147, 15p

Subject Terms: KNAPSACK problems, PROBLEM solving, SET theory, COMBINATORIAL optimization, EVOLUTIONARY algorithms, GENETIC algorithms

Augmenting bi-objective branch and bound by scalarization-based information.

Authors: Bauß, Julius Stiglmayr, Michael

Source: Mathematical Methods of Operations Research; Aug2024, Vol. 100 Issue 1, p85-121, 37p

Subject Terms: BRANCH & bound algorithms, INTEGER programming, INTEGERS

Sensitivity Analysis of the Cost Coefficients in Multiobjective Integer Linear Optimization.

Authors: Andersen, Kim Allan Boomsma, Trine Krogh Efkes, Britta et al.

Source: Management Science; Feb2025, Vol. 71 Issue 2, p1120-1137, 18p

Subject Terms: LINEAR programming, MULTI-objective optimization, KNAPSACK problems, INTEGER programming, CONVEX sets

Chaotic vegetation evolution: leveraging multiple seeding strategies and a mutation module for global optimization problems.

Authors: Zhong, Rui Zhang, Chao Yu, Jun

Source: Evolutionary Intelligence; Aug2024, Vol. 17 Issue 4, p2387-2411, 25p

Compressed representation for higher-level meme space evolution: a case study on big knapsack problems.

Authors: Feng, Liang Gupta, Abhishek Ong, Yew-Soon

Source: Memetic Computing; Mar2019, Vol. 11 Issue 1, p3-17, 15p

Optimizing with Attractor: A Tutorial.

Authors: Li, Weiqi

Source: ACM Computing Surveys; Sep2024, Vol. 56 Issue 9, p1-41, 41p

Subject Terms: MICROSOFT Visual Basic (Computer program language), INFORMATION theory, ATTRACTORS (Mathematics), OPTIMIZATION algorithms, POLYNOMIAL time algorithms, TRAVELING salesman problem, ANT algorithms, DEEP learning, KNAPSACK problems

An efficient relax-and-solve method for the multi-mode resource constrained project scheduling problem.

Authors: Etminaniesfahani, Alireza Gu, Hanyu Naeni, Leila Moslemi et al.

Source: Annals of Operations Research; Jul2024, Vol. 338 Issue 1, p41-68, 28p

Subject Terms: MATHEMATICAL programming, KNAPSACK problems, NP-hard problems, SCHEDULING, CONSTRAINT programming

Computationally efficient evolutionary optimisation for joint reservoir design-operations.

Authors: Motevali Bashi Naeini, Elaheh Soltaninia, Shahrokh

Source: Proceedings of ICE: Water Management; Jun2023, Vol. 176 Issue 3, p132-147, 16p

Effect of learning strategies in an evolutionary method: the case of the bi-objective quadratic multiple knapsack problem.

Authors: Aïder, Méziane Gacem, Oussama Hifi, Mhand

Source: Neural Computing & Applications; Jan2023, Vol. 35 Issue 2, p1183-1209, 27p

Subject Terms: KNAPSACK problems, LEARNING strategies, COMBINATORIAL optimization, BACKPACKS, GENETIC algorithms