Plenary Speakers

My T. Thai (University of Florida, United States)

Title: Accelerating Viral Marketing: From Combinatorial Strategies to Learning-Based Solutions

The landscape of viral marketing is evolving rapidly, demanding innovative approaches to maximize influence and cost-effectiveness in billion-scale networks. This keynote explores cutting-edge advancements in viral marketing optimization, transcending traditional combinatorial approaches to learning-based strategies. Our journey begins with a traditional (1-1/e)-approximation algorithm with accelerated sampling frameworks, further demonstrating an almost exact solution for this NP-hard problem. Shifting gears to heterogeneous multiplex networks, we introduce combinatorial algorithms that effectively navigate complex overlapping user dynamics, capturing the influences between and within multiple networks. Embracing machine learning, we unveil a transformative framework designed to overcome fundamental obstacles in traditional non-learning-based approaches. Finally, our exploration concludes with MIM-Reasoner, which exploits the reinforcement learning with probabilistic graphical models to address the viral marketing across various platforms.

Thomas Magnanti (MIT, United States)

Title: Designing Transportation and Telecommunications Networks

Network design is a broad topic that has many applications and poses many challenges for the field of combinatorial optimization. The basic issue is to meet the delivery of goods ( e.g., people, freight, messages) from sources to destinations by constructing a network of physical links or routes that incur a fixed cost for installation. The links or routes might be capacitated and the network might have special structure. In this presentation I will discuss some combinatorial and integer programming issues and results, with an emphasis on transportation and telecommunications networks.

El-Ghazali Talbi (Université de Lille, France)

Title: Metaheuristics for the automated design and configuration of Deep Neural Networks

In recent years, research in metaheuristic optimization approaches in the automatic design and configuration of deep neural networks has become increasingly popular. Although various approaches have been proposed, there is a lack of a comprehensive survey and taxonomy on this hot research topic. In this talk, we propose a unified way to describe the various metaheuristics that focus on common and important search components of optimization algorithms: representation, objective function, constraints, initial solution(s), and variation operators. In addition to large-scale search space, the problem is characterized by its variable mixed design space, it is very expensive, and it has multiple blackbox objective functions. Hence, this unified methodology has been extended to advanced optimization approaches, such as surrogate-based, multi-objective, and parallel optimization.

Stefan Irnich (Johannes Gutenberg University Mainz, Germany)

Title: Shortest Path Problems With Resource Constraints

In most vehicle routing and crew scheduling problems solved by column generation-based methods, the subproblem is a variant of the shortest path problem with resource constraints (SPPRC). The SPPRC has contributed to the success of these methods in at least two ways: First, its resource constraints provide a flexible tool for modeling complex cost structures as well as a wide variety of rules that define the feasibility of a route or a schedule. Second, efficient algorithms are available for at least for some important variants of the SPPRC. The talk presents selected examples of modeling with SPPRC and an overview of state-of-the-art methods for solving SPPRC.
Supported by FWO Scientific Research Community OR4Logistics (grant number W001321N).

Abstract Submissions

Abstract submission is CLOSED

For each submitted paper, ONE unique registration must be submitted as well (e.g., for two submitted papers, two separate registrations must be submitted).

Registration

Registration type	Cost (€)
Regular Early Registration until: May 10th, 2024	220
Regular Late Registration until: May 25th, 2024	275
Student Early Registration until: May 10th, 2024	155
Student Late Registration until: May 25th, 2024	220
Accompanying person registration (Conference dinner & Social event) until: May 25th, 2024	120

Early registration for ECCO 2024 is now OPEN and can be done by completing the registration form.
After submitting the form, you will receive two emails: one with the payment details and another with the registration details. If you do not receive these emails, please check your spam folder or contact [email protected].

Transfer costs (e.g., credit card fees, etc.) are not included in the registration fee and are paid by the delegate.

Special Student Rate: 20 master/PhD students will be supported and can apply for the Special Student Rate. To qualify for the Special Student Rate, students need to provide official evidence of their studentship from their institution on a stamped letterhead. Student applications with their university certificates should be submitted by email by April 18th. The announcement of the acceptance/rejection of the applications will be made by April 22th.

The category (early/late) of the registration fees are determined by the date the payment is made, not the date of registration.

Cancellation policy: The registration of participation is binding. Cancellation of registration must be submitted in writing via email. Cancellations received before May 25^th 2024 are subject to a 20% administrative fee. No refunds will be paid after May 25^th 2024.

Scientific & Social Programs

The Conference will take place between Thursday June 6^th and Saturday June 8^th 2024.

Programme of Talks

• The conference program is not available yet.
• The Registration Desk will be open on Thursday June 6^th at 8am.

Social Events

• Conference Dinner: On Friday June 7^th at Pakhuis
• TO BE ANNOUNCED