Search Results - Branch and bound Knapsack problem Multiobjective Evolutionary 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

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

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

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

Improving the performance of evolutionary algorithms for the multiobjective 0/1 knapsack problem using ɛ -dominance.

Authors: Grosan, C.

Source: Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753); 2004, p1958-1958, 1p

Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem.

Authors: Mahrach, Mohammed Miranda, Gara León, Coromoto et al.

Source: Mathematics (2227-7390); Nov2020, Vol. 8 Issue 11, p2018-2018, 1p

Subject Terms: TRAVELING salesman problem, KNAPSACK problems, PROBLEM solving, EVOLUTIONARY algorithms, EVOLUTIONARY computation

An exploratory research of elitist probability schema and its applications in evolutionary algorithms.

Authors: Zhang, Hong-Guang Liu, Yuan-An Tang, Bi-Hua et al.

Source: Applied Intelligence; Jun2014, Vol. 40 Issue 4, p695-709, 15p

Subject Terms: COMBINATORIAL optimization, GENETIC algorithms, GENETIC programming, PARTICLE swarm optimization, SWARM intelligence

Players’ selection for basketball teams, through Performance Index Rating, using multiobjective evolutionary algorithms.

Authors: Pérez-Toledano, Miguel Ángel Rodriguez, Francisco J. García-Rubio, Javier et al.

Source: PLoS ONE; 9/4/2019, Vol. 14 Issue 9, p1-20, 20p

Subject Terms: EVOLUTIONARY algorithms, BASKETBALL teams, SPORTS competitions, SPORTS administration, BIOLOGICAL evolution, DIFFERENTIAL evolution

Geographic Terms: SPAIN

Company/Entity: EUROPEAN Union

Multiobjective Optimization and Evolutionary Algorithms for the Application Mapping Problem in Multiprocessor System-on-Chip Design.

Authors: Erbas, Cagkan Cerav-Erbas, Selin Pimentel, Andy D.

Source: IEEE Transactions on Evolutionary Computation; Jun2006, Vol. 10 Issue 3, p358-374, 17p, 3 Diagrams, 4 Charts, 11 Graphs

Subject Terms: COMPUTER software, EMBEDDED computer systems, INTEGER programming, CASE studies, MATHEMATICAL mappings, INHOMOGENEOUS materials

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

Authors: Florios, Kostas Mavrotas, George Diakoulaki, Danae

Relation: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00497-4

Availability: http://www.sciencedirect.com/science/article/pii/S0377-2217(09)00497-4

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

Considerations in Engineering Parallel Multiobjective Evolutionary Algorithms.

Authors: Van Veldhuizen, David A. Zydallis, Jesse B. Lamont, Gary B.

Source: IEEE Transactions on Evolutionary Computation; Apr2003, Vol. 7 Issue 2, p144, 30p

Subject Terms: ALGORITHMS, RESEARCH, SYMMETRIC domains, MATHEMATICAL notation

QUANTUMIZED GENETIC ALGORITHM FOR SEGMENTATION AND OPTIMIZATION TASKS.

Authors: Sabeti, Malihe Karimi, Laleh Honarvar, Naemeh et al.

Source: Biomedical Engineering: Applications, Basis & Communications; Jun2020, Vol. 32 Issue 03, pN.PAG-N.PAG, 11p

Subject Terms: IMAGE segmentation, GENETIC algorithms, PARTICLE swarm optimization, MATHEMATICAL optimization, THRESHOLDING algorithms, COMPUTER vision

Concrete hyperheuristic framework for test case prioritization.

Authors: Bian, Yi Li, Zheng Guo, Junxia et al.

Source: Journal of Software: Evolution & Process; Nov2018, Vol. 30 Issue 11, pN.PAG-N.PAG, 1p

Subject Terms: REGRESSION testing (Computer science), ITERATIVE methods (Mathematics), EVOLUTIONARY algorithms, LEARNING strategies, HEURISTIC

Scheduling multi-configuration last-mile delivery logistics by learning from optimisation feedback and customer preferences.

Authors: Tafakkori, Keivan Tavakkoli-Moghaddam, Reza Siadat, Ali

Source: International Journal of Production Research; Nov2025, Vol. 63 Issue 21, p7835-7864, 30p

Subject Terms: LOGISTICS, SCHEDULING, DELIVERY of goods, PREDICTION models, OPERATIONS research, CONSUMER preferences, EVOLUTIONARY 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

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

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

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

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