Solving bin packing problem based on parallel hybrid genetic algorithm

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dc.contributor.advisorÇevik, Mesut
dc.contributor.authorAbdulkareem, Mohammed Husham
dc.date.accessioned2023-09-07T07:33:47Z
dc.date.available2023-09-07T07:33:47Z
dc.date.issued2022en_US
dc.date.submitted2022
dc.departmentEnstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalıen_US
dc.description.abstractThe use of heuristic search is essential to the field of artificial intelligence and is required in order to find solutions to problems that arise in knowledge-based operations. The purpose of the Bin Packing Problem (BPP) is to identify the fewest number of boxes that are necessary to package a group of items of specified sizes into a given collection of bins without exceeding the capacity of any individual bin. It is well acknowledged that NP-Hard problem. In this study, we present a hybrid genetic algorithm that employs BFD in order to deal with infeasible solution sets brought about by the bin-used format (Best Fit Decreasing). We discussed our experiences developing parallel solutions to the (BPP). Investigation into alternative bin packing strategies is being done in order to have a better grasp of the challenges associated with resource allocation.as well as the different ways that different packing algorithms affect the effectiveness of packing. The apparent serial nature of packing bins has been modelled, and this modelling has prevented past studies from growing beyond their limits of many thousands of containers. We demonstrate this with data that is not very complicated. It is not impossible for parallel algorithms to achieve linear speedup. Simulations of up to hundreds of sizes for a wide range of characteristics have been simulated, along with thousands of bins and heuristics, our approach to dealing with impossible chromosomes was shown to be effective by experimental data, which helped to raise the bar. Academics have found that the behaviours of the bin packing problem are highly complex, despite the fact that it initially presents itself as an easy problem to solve by coordinating the measurements of the object's length, height, or width with those of the available packing space., the planned packing method aims to reduce the number of boxes voids produced during the packing process. In order to come up with this packing strategy, HGA was used to solve the problem. The findings of the technique that was suggested were reviewed and then compared to multiple sets of Arithmetic results identified in academic journals that were related to the answer that was reached. In the classic boxing problem, you are tasked with fitting a predetermined quantity of objects into a set of containers that are all of the same size. This is done to cut down on the number of boxes that need to be used and to make sure that the total size of the things inside each box doesn't go over the box's capacity.en_US
dc.identifier.citationAbdulkareem, Mohammed Husham. (2022). Solving bin packing problem based on parallel hybrid genetic algorithm. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12939/3867
dc.identifier.yoktezid796392
dc.institutionauthorAbdulkareem, Mohammed Husham
dc.language.isoen
dc.publisherAltınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsüen_US
dc.relation.publicationcategoryTezen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGenetic Algorithmen_US
dc.subjectBin Backing Problemen_US
dc.subjectParallel Strategyen_US
dc.subjectThree-Dimensional Bin Packingen_US
dc.subjectHGAen_US
dc.subjectDBPLen_US
dc.titleSolving bin packing problem based on parallel hybrid genetic algorithm
dc.typeMaster Thesis

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