How good are convex hull algorithms?
Computational Geometry: Theory and Applications
Heuristic and Metaheuristic Approaches for a Class of Two-Dimensional Bin Packing Problems
INFORMS Journal on Computing
A new heuristic recursive algorithm for the strip rectangular packing problem
Computers and Operations Research
A New Placement Heuristic for the Orthogonal Stock-Cutting Problem
Operations Research
The Bottomn-Left Bin-Packing Heuristic: An Efficient Implementation
IEEE Transactions on Computers
A Simulated Annealing Enhancement of the Best-Fit Heuristic for the Orthogonal Stock-Cutting Problem
INFORMS Journal on Computing
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This paper presents an aircraft load allocation optimisation model, which uses a hybrid of simulated annealing and genetic algorithm methods to solve a multi-objective optimisation problem associated with allocating a set of cargo items across a heterogeneous fleet of available airlift assets. It represents candidate solutions using macrochromosomes comprised of an ordered list of available transport assets followed by an ordered list of cargo items. A bin packing heuristic is used to map each individual to a point in asset-utilization space where a novel convex hull based fitness function is used to evaluate the relative quality of each individual and drive an elitist application of genetic operators on the population--including a novel extinction operation that infrequently culls solutions comprising of aircraft chalks that cannot be load balanced. Proof of concept computational results are presented.