Pages that link to "Item:Q2875120"

The following pages link to Exploration and exploitation in evolutionary algorithms: a survey (Q2875120):

Displaying 50 items.

• A review of chaos-based firefly algorithms: perspectives and research challenges (Q298693) (← links)
• Using multi-objective evolutionary algorithms for single-objective optimization (Q385470) (← links)
• On clarifying misconceptions when comparing variants of the artificial bee colony algorithm by offering a new implementation (Q508802) (← links)
• Hybrid evolutionary algorithm for the b-chromatic number (Q525060) (← links)
• Prioritized surgery scheduling in face of surgeon tiredness and fixed off-duty period (Q887888) (← links)
• Auto-tuning strategy for evolutionary algorithms: Balancing between exploration and exploitation (Q1006910) (← links)
• A developed artificial bee colony algorithm based on cloud model (Q1649145) (← links)
• Diversity controlling genetic algorithm for order acceptance and scheduling problem (Q1718199) (← links)
• COOBBO: a novel opposition-based soft computing algorithm for TSP problems (Q1736627) (← links)
• Across neighborhood search for numerical optimization (Q1750545) (← links)
• Fractional calculus-based firefly algorithm applied to parameter estimation of chaotic systems (Q2000333) (← links)
• Quantum-behaved particle swarm optimization with collaborative attractors for nonlinear numerical problems (Q2005042) (← links)
• Novelty search for global optimization (Q2008571) (← links)
• Diversity metrics for direct-coded variable-length chromosome shortest path problem evolutionary algorithms (Q2019686) (← links)
• Decomposition-based evolutionary algorithm with automatic estimation to handle many-objective optimization problem (Q2055580) (← links)
• Enhancing gene expression programming based on space partition and jump for symbolic regression (Q2056306) (← links)
• Stochastic multiple chaotic local search-incorporated gradient-based optimizer (Q2065423) (← links)
• The trap of Sisyphean work in differential evolution and how to avoid it (Q2086554) (← links)
• Learning-based multi-objective evolutionary algorithm for batching decision problem (Q2108120) (← links)
• Global sensing search for nonlinear global optimization (Q2124800) (← links)
• A novel version of slime mould algorithm for global optimization and real world engineering problems. Enhanced slime mould algorithm (Q2140055) (← links)
• EST-TSA: an effective search tendency based to tree seed algorithm (Q2163738) (← links)
• Differential evolution with enhanced diversity maintenance (Q2192995) (← links)
• A diversity enhanced multiobjective particle swarm optimization (Q2195449) (← links)
• Meta-optimization of multi-objective population-based algorithms using multi-objective performance metrics (Q2212577) (← links)
• Balancing exploration and exploitation in multiobjective evolutionary optimization (Q2215078) (← links)
• A similarity-based neighbourhood search for enhancing the balance exploration-exploitation of differential evolution (Q2297562) (← links)
• An evolutionary approach to optimizing teleportation cost in distributed quantum computation (Q2308427) (← links)
• Levy distributed parameter control in differential evolution for numerical optimization (Q2311234) (← links)
• Integrated rescheduling and preventive maintenance for arrival of new jobs through evolutionary multi-objective optimization (Q2402113) (← links)
• Exploration/exploitation tradeoff with cell-shift and heuristic crossover for evolutionary algorithms (Q2461333) (← links)
• Learning paradigm based on jumping genes: a general framework for enhancing exploration in evolutionary multiobjective optimization (Q2510182) (← links)
• Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization (Q2630818) (← links)
• A review on complex system engineering (Q2661837) (← links)
• Dealing with multi-modality using synthesis of moth-flame optimizer with sine cosine mechanisms (Q2664799) (← links)
• Honey badger algorithm: new metaheuristic algorithm for solving optimization problems (Q2666510) (← links)
• A weighted-sum method for solving the bi-objective traveling thief problem (Q2669668) (← links)
• (Q4436816) (← links)
• A new hypervolume-based differential evolution algorithm for many-objective optimization (Q4578176) (← links)
• Performance of Sine–Cosine Algorithm on Large-Scale Optimization Problems (Q4613894) (← links)
• A branch-and-bound algorithm based on NSGAII for multi-objective mixed integer nonlinear optimization problems (Q6048167) (← links)
• Toward explicit control between exploration and exploitation in evolutionary algorithms: a case study of differential evolution (Q6074958) (← links)
• Balanced-evolution genetic algorithm for combinatorial optimization problems: the general outline and implementation of balanced-evolution strategy based on linear diversity index (Q6084237) (← links)
• Adaptive evolutionary algorithms for portfolio selection problems (Q6088765) (← links)
• An adaptive fuzzy penalty method for constrained evolutionary optimization (Q6092068) (← links)
• A new taxonomy of global optimization algorithms (Q6137180) (← links)
• A diversity metric for population-based metaheuristic algorithms (Q6154454) (← links)
• Multi-strategy improved artificial rabbit optimization algorithm based on fusion centroid and elite guidance mechanisms (Q6497155) (← links)
• Active learning-assisted multi-fidelity surrogate modeling based on geometric transformation (Q6550154) (← links)
• An advanced initialization technique for metaheuristic optimization: a fusion of Latin hypercube sampling and evolutionary behaviors (Q6552680) (← links)