Metaheuristics

This volume constitutes the refereed proceedings of Metaheuristics on 15th International Conference, MIC 2024, held in Lorient, France, during June 47, 2024.

The 36 full papers presented together with 34 short papers were carefully reviewed and selected from 127 submissions. The conference focuses on artificial intelligence, combinatorial optimization, computer science, graph theory, evolutionary algorithms, genetic algorithms, simulated annealing, optimization, optimization problems.

Inhalt

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.