Open Access selected Papers

IEEE Open Access

IEEE Transactions on Emerging Topics in Computational Intelligence now offers publication of its highlighted papers in Open Access for the duration of 3 months in order to assist authors gain maximum exposure for their groundbreaking research and application-oriented papers to all reader communities.

The fourth highlighted paper offered to make Open Access in TETCI is now available for the duration of 3 months starting from 1 October 2019.


New Shades of the Vehicle Routing Problem: Emerging Problem Formulations and Computational Intelligence Solution Methods
Authors: Jacek Mańdziuk
Publication: IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
Issue: Volume 3, Issue 3 – June 2019
Pages: 230-244

Abstract: This paper presents an overview of recent advances in the field of the vehicle routing problem (VRP), based on papers published in high-quality journals during the period from January 2015 to July 2017. A distinctive feature of the presented survey is its focus on new versions of the VRP, which have recently emerged or gained momentum, and the corresponding new solution methods, with particular emphasis on computational intelligence (CI) approaches. The list of newly proposed or currently popular VRP formulations include last mile and same day delivery, crowdshipping, bike sharing systems, post-disaster response plans, local routing in large production or cargo plants, customer-centric VRP, autonomous delivery, unnamed aerial vehicle delivery, green VRP, waste collection VRP, rich VRP, or VRP with backhauls. Simultaneously, an adequate increase of interest in the application of traditional CI methods (e.g., genetic, memetic, ant colony or particle swarm optimization, simulated annealing, or their various hybrid versions) can be observed in the VRP domain. At the same time, approaches proven efficient in other optimization areas (e.g., hyperheuristics, methods based on Monte Carlo simulations, algorithms rooted in game theory and bi-level optimization – Stackelberg games, or cognitively motivated methods) have lately entered the VRP field and become a viable alternative to more traditional techniques. Since VRP is one of the fastest growing fields in the operations research area, we believe that an analysis of the recently published VRP papers from the perspective of their novelty in problem formulation and/or applied solution method can provide a true value for the CI community, especially young researchers entering the field and seeking challenges in this interesting and fast developing research area.

Index Terms: Computational intelligence, Vehicle routing, Combinatorial optimization, Metaheuristics
IEEE Xplore Link: https://ieeexplore.ieee.org/document/8591961


Available in Open Access from 1 October 2019 to 30 December 2019 in IEEE Xplore Digital Library.


Previous Open Access selected Papers

Light Gated Recurrent Units for Speech Recognition
Authors: Mirco Ravanelli, Philemon Brakel, Maurizio Omologo and Yoshua Bengio
Publication: IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
Issue: Volume 2, Issue 2 – April 2018
Pages: 92-102
Index Terms: Speech recognition, Deep learning, Recurrent neural networks, LSTM, GRU
IEEE Xplore Link: https://ieeexplore.ieee.org/document/8323308

End-to-End Learning for Physics-Based Acoustic Modeling
Authors: Leonardo Gabrielli, Stefano Tomassetti, Carlo Zinato and Francesco Piazza
Publication: IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
Issue: Volume 2, Issue 2 – April 2018
Pages: 160-170
Index Terms: Physics-based acoustic modeling, End-to-end learning, Convolutional neural networks
IEEE Xplore Link: https://ieeexplore.ieee.org/document/8323323

An All-Memristor Deep Spiking Neural Computing System: A Step Toward Realizing the Low-Power Stochastic Brain
Authors: Parami Wijesinghe, Aayush Ankit, Abhronil Sengupta and Kaushik Roy
Publication: IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)
Issue: Volume 2, Issue 5 – October 2018
Pages: 345-358
Index Terms: Memristor, Stochasticity, Deep stochastic spiking neural networks
IEEE Xplore Link: https://ieeexplore.ieee.org/document/8471280