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Selective Survey: Most Efficient Models and Solvers for Integrative Multimodal Transport
The main objective is to explore a beneficent selection of the existing research, methods and information in the field of multimodal transportation research, to identify industry needs and gaps in research and provide context for future research.
A glass-box interactive machine learning approach for solving NP-hard problems with the human-in-the-loop
The goal of Machine Learning to automatically learn from data, extract knowledge and to make decisions without any human intervention.
On the Resilience of an Ant-based System in Fuzzy Environments. An Empirical Study
The current work describes an empirical study conducted in order to investigate the behavior of an optimization method in a fuzzy environment.
The Generalized Traveling Salesman Problem solved with Ant Algorithms
A well known N P-hard problem called the Generalized Traveling Salesman Problem (GTSP) is considered.
A Unifying Survey of Reinforced, Sensitive and Stigmergic Agent-Based Approaches for E-GTSP
The Generalized Traveling Salesman Problem (GTSP) is one of the NP-hard combinatorial optimization problems.
