Perspective Directions of Artificial Intelligence Systems in Aircraft Load Optimization Process

Perspective Directions of Artificial Intelligence Systems in Aircraft Load Optimization Process

Yelyzaveta Serhiyivna Sahun (Flight Academy, National Aviation University, Ukraine)
DOI: 10.4018/978-1-7998-1415-3.ch018


The chapter represents an overview of different approaches towards loading process and load planning. The algorithm and specificities of the current cargo loading process force the scientists to search for new methods of optimizing due to the time, weight, and size constraints of the cargo aircraft and consequently to cut the costs for aircraft load planning and handling procedures. These methods are based on different approaches: mix-integer linear programs, three-dimensional bin packing, knapsack loading algorithms, tabu-search approach, rule-based approach, and heuristics. The perspective direction of aircraft loading process improvement is a combination of multicriteria optimization method and heuristic approach using the expert system.
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It splits to different types of loading sub problems, as a The Bin-Packing Problem (BPP), Container Loading Problem (CLP), Knapsack Problem (KP), and Assignment.

The Bin-Packing Problem (BPP) is the loading problem which deals with packing objects of different sizes into a précised number of similar bins, such that the number of used bins is minimized. The problem is well-known as nondeterministic polynomial time problem (NP-hard) and difficult to solve in practice, especially when dealing with the multi-dimensional cases. (Paquay, Schyns, Limbourg, 2011) mention that the BPP can be one, two or three dimensional and with one or several containers. If there are several containers, they can have the same or different shapes (Dyckho, 1990).

Container Loading Problem (CLP) closely correlates with BPP. Authors search the ways how to optimize a space assignment of cargo inside the container, with the objective to maximize the value of the cargo or aircraft’s capacity. The container loading problems can be divided into two types. The first is three-dimensional bin-packing problem. (Bortfeldt & Mack, 2007) note, that the point of the problem, is reducing the number of used containers. The other work (Bortfeldt & Gehring, 2001) defines the second problem as a knapsack problem and its objective is to maximize the capacity of the container while packing to it the cargo which has more value. The CLP focuses on a single container, and has been extended in the literature to handle a variety of different constraints arising from real-world problems. Consider for example the problem of arranging items into an aircraft cargo area such that the barycenter of the loaded plane is as close as possible to an ideal point given by the aircraft's specifications. The position of the barycenter has an impact on the flight performance in terms of safety and efficiency, and even a minor displacement from the ideal barycenter can lead to a high increase of fuel consumption (Trivella & Pisinger, 2017). The other group of loading challenges is a Knapsack Problem (KP). The single-objective knapsack problem consists of choosing a subset of objects from a defined set, maximizing the overall profit, which results from the sum of the individual benefits of the selected objects where a capacity constraint must be fulfilled, i.e., the sum of the weights of the selected objects, must not surpass a given capacity (Martello, Toth, 1990; Kellerer, Pferschy, Pisinger, 2004).

Key Terms in this Chapter

Modus Ponens: The rule of logic that says that if a conditional statement (“if-then”) is accepted.

Container Loading Problem (KLP): A problem that define a loading of the set of rectangular boxes into a rectangular bin of fixed dimensions in order to maximize the volume of the boxes.

Knowledge Base (KB): Technology used to store structured and unstructured data used by the computer system.

Block Relocation Problem with Weights (BRPW): A study, which deals with the problem of block replacement (closely correlates with a Bin Packing Problem).

Unit Load Device (ULD): An assembly of components consisting of a container or of a pallet covered with a net, whose purpose is to provide standardized size units for individual pieces of baggage or cargo for rapid loading and unloading.

Modus Tolens: A valid form of argument in which the consequent of a conditional proposition is denied, thus implying the denial of the antecedent.

Bin Packing Problem (BPP): A problem that define items of different volumes which have to be packed into a definite number of bins of finite volume in such a way that minimizes the number of bins used in the aircraft cargo compartment.

Artificial Intelligence System (AIS): Computer system, that simulate human intelligence processes: learning, reasoning and self-correction.

Knowledge-Based Systems (KBS): Computer system that generates and uses knowledge from different data, sources and information.

SQL-server: A relational database management system created by Microsoft.

Expert system (ES): Artificial intelligence system that converts the knowledge of an expert in a specific subject into a software code.

Knapsack Problem (KP): problem in combinatorial optimization which solve how the chosen set of items, with parameters of weight and a value, should be loaded in a way so that the total weight is less or equal to a set aircraft constraints and the total value is as large as possible.

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