Search Results for author: Divyam Aggarwal

Found 4 papers, 0 papers with code

A Novel Column Generation Heuristic for Airline Crew Pairing Optimization with Large-scale Complex Flight Networks

no code implementations18 May 2020 Divyam Aggarwal, Dhish Kumar Saxena, Saaju Pualose, Thomas Bäck, Michael Emmerich

Crew Pairing Optimization (CPO) is critical for an airlines' business viability, given that the crew operating cost is second only to the fuel cost.

Combinatorial Optimization

On Learning Combinatorial Patterns to Assist Large-Scale Airline Crew Pairing Optimization

no code implementations28 Apr 2020 Divyam Aggarwal, Yash Kumar Singh, Dhish Kumar Saxena

Airline Crew Pairing Optimization (CPO) aims at generating a set of legal flight sequences (crew pairings), to cover an airline's flight schedule, at minimum cost.

On Initializing Airline Crew Pairing Optimization for Large-scale Complex Flight Networks

no code implementations15 Mar 2020 Divyam Aggarwal, Dhish Kumar Saxena, Thomas Bäck, Michael Emmerich

Even generating an initial feasible solution (IFS: a manageable set of legal pairings covering all flights), which could be subsequently optimized is a difficult (NP-complete) problem.

Real-World Airline Crew Pairing Optimization: Customized Genetic Algorithm versus Column Generation Method

no code implementations8 Mar 2020 Divyam Aggarwal, Dhish Kumar Saxena, Thomas Back, Michael Emmerich

In a significant departure, this paper considers over 800 flights of a US-based large airline (with a monthly network of over 33, 000 flights), and tests the efficacy of GAs by enumerating all 400, 000+ crew pairings, apriori.

Combinatorial Optimization

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