Metaheuristics

Metaheuristics

15th International Conference, MIC 2024, Lorient, France, June 4-7, 2024, Proceedings, Part I

Sifaleras, Angelo; Sevaux, Marc; Makboul, Salma; Olteanu, Alexandru-Liviu; Pardo, Eduardo G.

Springer International Publishing AG

06/2024

399

Mole

9783031629112

15 a 20 dias

Descrição não disponível.
Advances in Combinatorial Optimization.- Breakout Local Search for Heaviest Subgraph Problem.- A Biased Random Key Genetic Algorithm for solving the ? neighbor p center problem.- A Continuous GRASP Random Key Optimizer.- Adaptive Ant Colony Optimization Using Node Clustering with Simulated Annealing.- Job Shop Scheduling with robot synchronization for transport operations.- AI and metaheuristics for routing.- SIRO A deep learning based next generation optimizer for solving global optimization problems.- Investigation of the Benefit of Extracting Patterns from Local Optima to solve a Bi objective VRPTW.- A Memetic Algorithm for Large Scale Real World Vehicle Routing Problems with Simultaneous Pickup and Delivery with Time Windows.- Tabu Search for Solving Covering Salesman Problem with Nodes and Segments.- GRASP with PATH RELINKING.- VNS with Path Relinking for the Profitable Close Enough Arc Routing Problem.- Meta heuristics for preference learning.- A simulated annealing algorithm to learn an RMP preference model.- New VRP and extensions.- Iterative Heuristic over Periods for the Inventory Routing Problem.- Combining Heuristics and Constraint Programming for the Parallel Drone Scheduling Vehicle Routing Problem with Collective Drones.- Operations Research for Health Care.- A Re optimization Heuristic for a Dial a Ride Problem in the Transportation of Patients.- Solving the Integrated Patient to Room and Nurse to Patient Assignment by Simulated Annealing.- Enhancing Real World Applicability in Home Healthcare A Metaheuristic Approach for Advanced Routing and Scheduling.- Solving the Two Stage Robust Elective Patient Surgery Planning under Uncertainties with Intensive Care Unit Beds Availability.- Extracting White box Knowledge from Word Embedding Modeling as an Optimization Problem.- A hybrid biased randomized heuristic for a home care problem with team scheme selection.- Optimization for forecasting.- Extended set covering for time series segmentation.- Quantum meta heuristic for Operations Research.- Indirect Flow Shop coding using rank application to Indirect QAOA.- Utilizing Graph Sparsification for Pre processing in Max Cut QUBO Solver.- Addressing Machine Unavailability in Job Shop Scheduling A Quantum Computing Approach.- Solving Edge weighted Maximum Clique problem with DCA warm start Quantum Approximate Optimization Algorithm.- Comparing Integer Encodings in QUBO for Quantum and Digital Annealing The Travelling Salesman Problem.- Solving Quadratic knapsack problem with biased quantum state Optimization Algorithm.- Quantum Optimization Approach for Feature Selection in Machine Learning.- International Conference on Variable Neighborhood Search (ICVNS).- Advanced Algorithms for the Reclaimer Scheduling Problem with Sequence Dependent Setup Times and Availability Constraints.- An efficient algorithm for the T row facility layout problem.- Interpretability Adaptability and Scalability of Variable Neighborhood Search.- Exploring the integration of General Variable Neighborhood Search with exact procedures for the optimization of the Order Batching Problem.- VNS based matheuristic approach to Group Steiner Tree with problem specific node release strategy.- A Basic Variable Neighborhood Search for the planar Obnoxious Facility Location Problem.- Temporal Action Analysis in Metaheuristics A Machine Learning Approach.- A variable neighborhood search approach for the S labeling problem.- Improving Biased Random Key Genetic Algorithm with Variable Neighborhood Search for the Weighted Total Domination Problem.- Optimization of fairness and accuracy on Logistic Regression models.- A Variable Formulation Search Approach for Three Graph Layout Problems.
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artificial intelligence;combinatorial optimization;computer science;graph theory;evolutionary algorithms;genetic algorithms;simulated annealing;optimization;optimization problems