By Ioannis Hatzilygeroudis, Vasile Palade, Jim Prentzas
Complex difficulties often can't be solved by means of person equipment or suggestions and require the synergism of a couple of of them to be solved. This e-book provides a few present efforts that use combos of equipment or strategies to unravel complicated difficulties within the components of sentiment research, seek in GIS, graph-based social networking, clever e-learning structures, info mining and suggestion structures. such a lot of them are attached with particular functions, while the remaining are mixtures in line with ideas. many of the chapters are prolonged models of the corresponding papers awarded in CIMA-15 Workshop, which came about along side IEEE ICTAI-15, in November 2015. the remainder are invited papers that answered to big demand papers for the ebook. The e-book is addressed to researchers and practitioners from academia or undefined, who're drawn to utilizing mixed tools in fixing advanced difficulties within the above areas.
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Extra info for Advances in Combining Intelligent Methods: Postproceedings of the 5th International Workshop CIMA-2015, Vietri sul Mare, Italy, November 2015 (at ICTAI 2015)
Society for Industrial and Applied Mathematics, Philadelphia, PA (2001) 5. : Some complexity results for the traveling salesman problem. In: STOC’76 Proceedings of the Eighth Annual ACM Symposium on Theory of Computing, pp. 1–9 (1976) 6. : Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems. J. ACM 45(5), 753–782 (1998) 7. : Reducibility among combinatorial problems. W. ) Complexity of Computer Computations, Advances in Computer Research, pp. 85–103.
Technol. 2(2), 56–63 (2012) 64. : Bat algorithm: literature review and applications. Int. J. Bio-Inspired Comput. 5, 141–149 (2013) 65. : An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems, engineering applications of artiﬁcial intelligence (2015, in press) 66. : General k-opt submoves for the Lin-Kernighan TSP heuristic. Math. Program. Comput. 1(2–3), 119–163 (2009) 67. : Solving the Bottleneck Traveling Salesman Problem Using the Lin-Kernigan-Helsgaun Algorithm.
Industry, Logistics, Transportations face speciﬁc scenarios and need speciﬁc models and simulations. Uncertainty, randomness and technological advances (such as the use of drones, reminded below) made us look towards very new versions of the TSP. The Probabilistic Traveling Salesman Problem (PTSP) is a more difﬁcult variant of the classical TSP. It was introduced by Jaillet  and came from the necessity to adopt a model that takes into account the random real life phenomena : for many delivery companies that perform pickup and delivery, not all the customers require daily visits.