Technical presentation

by Steven Rushworth

Sponsor presentation

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Technical presentation

by Lana Jansen

Technical presentation: Autonomous orchestration of third-party optimisation engines for airline crew planning

by Meherzad (Maz) Lakadia

Optimisation engines are widely used in airline crew planning to generate solutions under operational constraints and business priorities. In practice, decision-making rarely relies on a single optimisation run. Analysts execute multiple scenarios to explore trade-offs, assess parameter sensitivity, and justify outcomes for specific operational contexts.
This calibration and scenario management process is typically performed manually by specialised analysts, becoming increasingly time-consuming as operations grow in scale or complexity. Modern engines efficiently solve individual problems, but much of the surrounding exploratory work remains outside the optimiser.
This presentation describes an autonomous orchestration approach applied to a commercial third-party crew planning optimisation engine. The orchestration layer operates externally, treating the optimiser as a black box and interacting only through its standard interface. It autonomously decides which optimisation runs to execute, adjusts parameters, rules, and input data across scenarios within allowable bounds, and determines when sufficient solution quality has been achieved. The system automates multi-scenario sensitivity analysis and trade-off exploration in a single end-to-end workflow.
Although demonstrated for crew planning, the methods are optimiser-agnostic and grounded in established OR and meta-optimisation techniques. The approach produces structured, human-readable insights that reduce manual analyst effort and improve the speed and consistency of optimisation-driven decision-making.

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Technical presentation: Evaluating Systemic Crew Risk and Operational Readiness Across Scheduling, Fatigue, and Crew Logistics

by Daniel Melendez

The future of crew management depends on understanding how scheduling decisions, fatigue exposure, crew accommodation, and operational efficiency interact as a single system. Many organizations optimize these elements independently, unintentionally masking systemic risks that only emerge during disruption or sustained operational pressure.
This presentation introduces a system-level evaluation approach that combines operations research, fatigue risk principles, and AI-based data analysis to assess crew risk and operational readiness end to end—from roster construction and duty sequencing to recovery opportunities, accommodation constraints, and disruption recovery.
The session demonstrates how these methods provide clear visibility into hidden systemic risks, enable a defensible risk and readiness score, and clarify where AI strengthens decision-making versus where it can introduce new risk if misapplied. Attendees will gain a decision-grade view of what degrades if nothing changes, supporting informed choices to ignore, patch, or intervene.

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Technical presentation: From Combinatorial Search to Sequential Validation: Achieving Real-Time Assignment in Preferential Bidding Systems

by Vigith Kartha, Mangesh Adgaonkar

Traditional airline PBS is NP-hard, requiring slow Branch-and-Price combinatorial search and resulting in opaque, batch-oriented bidding and crew dissatisfaction. This paper proposes a shift to a List-Based, Sequential Validation Assignment. By converting generic rules into a pre-sorted pairing list, the algorithm bypasses the time-consuming Pricing Problem of Column Generation. This breakthrough achieves speeds that make Interactive PBS (IPBS) operationally feasible, enabling continuous feedback. IPBS maximizes transparency, empowers crew to adjust bids, and directly enhances crew satisfaction. This List-Based approach advocates for a new standard in operational efficiency.

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