Hyper-heuristics are search methodologies that operate on a space of heuristics rather than directly on candidate solutions. Their key objective is to automate decision-making within optimisation algorithms, reducing the need for extensive problem-specific tuning while delivering high-quality solutions across a wide range of complex applications.

Transport and logistics systems routinely involve challenging optimisation problems, including vehicle routing, scheduling, timetabling, network design, resource allocation, and multimodal transportation planning. Traditional optimisation approaches often require significant expert knowledge and bespoke algorithm development. Hyper-heuristics offer an alternative by intelligently selecting and combining search operators, enabling more adaptive, reusable and effective optimisation strategies.

This session provides an accessible introduction to hyper-heuristics for attendees with little or no prior experience in the area. We will explain the fundamental concepts behind hyper-heuristics, discuss their relationship to modern optimisation and AI techniques, and illustrate how they can be applied to transportation and logistics problems. Drawing on examples from routing, scheduling, airline and flight planning, logistics operations, and other real-world case studies, we will demonstrate how hyper-heuristics can support effective decision-making in complex environments.

The session is aimed at both researchers and practitioners interested in learning how hyper-heuristic methods can be used to tackle challenging transport and logistics problems. No prior knowledge of hyper-heuristics is assumed.

Speakers: Ahmed Kheiri (University of Manchester) and Ender Ozcan (University of Nottingham)

CPD Hours - 2 Hours 

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