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[{"key": "dc.contributor.advisor", "value": "Br\u00e4ysy, Olli", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.advisor", "value": "Cochez, Michael", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Mian, Isfandyar Khan", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2020-07-10T03:57:44Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2020-07-10T03:57:44Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2020", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/71110", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Vehicle routing optimization and container loading combined would produce millions of queries for the remaining capacity of the vehicles. In this situation, these approximate methods for finding the remaining capacity of the vehicle\u2019s container are investigated.\nThese methods reduce the time needed to approximate the remaining capacity in vehicles and\nwill hence accelerate the overall optimization process. In this thesis we consider a solution\nto improve the accuracy of real-world vehicle routing optimization problems. Simple capacitated vehicle routing optimization does not capture any information about the packing of\nobjects except by deducting the volume of the packed objects from the container\u2019s volume.\nBin packing during the routing optimization is usually slow. We combine a very fast approximation algorithm for 3D bin packing with vehicle routing optimization to speed up the\nwhole process. Vehicle routing combined with the 3D container loading problem creates new\nkinds of challenges. The problem was introduced in Gendreau et al. 2006 where 3D loading\nspace replaces the scalar capacity of the vehicles. The container loading problem attempts to\nobtain the best possible utilization of space, while the vehicle routing problem is concerned\nwith finding the minimum-cost or minimum-distance route in transportation. The combined\nproblem is about loading boxes with different symmetry into rectangular containers of the\nvehicles used in delivery. This problem is extremely hard because it is a combination of\nthe two problems mentioned above, which are both NP-hard [Gendreau et al. 2006, Pisinger 2002]. Finding an exact solution for this problem is infeasible since even solving a small\ninstance of bin packing problem alone would require more computing resources as feasible\n(Martello, Pisinger, and Vigo 2000). To handle this situation approximation algorithms are\nused as it is often not necessary to find the optimal solution for the bin packing problem.\nAn approximate solution that is close to optimal and computed with the help of reasonable\nresources and time is considered a good solution. When vehicle routing optimization and\ncontainer loading are combined, a high number of queries for the remaining capacity of the\nvehicles are performed. In this thesis we exploit this fact and perform experiments with approximate methods for finding the remaining capacity of the vehicle\u2019s container in a fast but\napproximate way. In our experiments we use a slight modification of the 3D bin packing algorithm called Largest Area First Fit (LAFF) (G\u00fcrb\u00fcz et al. 2009) as a rough but fast means\nto determine the remaining capacity in the containers during the vehicle routing optimization process. A bounding box is used for objects which are not rectangular in shape, such as\ncylindrical shapes. The LAFF algorithm carries the placement of the boxes such that those\nwith the largest surface area are placed first while keeping the height minimum from the floor\nof the container. The box which covers the largest ground area of the container is placed first\nfollowed by subsequent boxes that are stacked in the remaining space at the same level, the\nboxes with the greatest volume first. Then the level is increased and the process repeated.\nBoxes are rotated such that they have the largest possible footprint. This algorithm works\nexceptionally fast when the number and variety of the objects to be packed are small. During\nthe LAFF stage, all real-world bin packing constraints e.g. the weight of the boxes, loading\npriorities, orientation, stacking, the distribution of weight in different parts of the container,\nstability, etc. are ignored to gain as much speed as possible.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Miia Hakanen (mihakane@jyu.fi) on 2020-07-10T03:57:44Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2020-07-10T03:57:44Z (GMT). No. of bitstreams: 0\n Previous issue date: 2020", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "93", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.format.mimetype", "value": "application/pdf", "language": null, "element": "format", "qualifier": "mimetype", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "Vehicle Routing Optimization", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Vehicle Loading Optimization", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Container Loading Optimization", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "Logistics Optimization", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Combining Vehicle Routing Optimization and Container Loading Optimization", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202007105284", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master\u2019s thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Informaatioteknologia", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Information Technology", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Tietotekniikka", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Mathematical Information Technology", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": "", "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "602", "language": "", "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "logistiikka", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "reititys", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "ajoneuvot", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "algoritmit", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "optimointi", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "matemaattinen optimointi", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "heuristiikka", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "logistics", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "routing", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "vehicles", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "algorithms", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "optimisation", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "mathematical optimisation", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "heuristic", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.format.content", "value": "fulltext", "language": null, "element": "format", "qualifier": "content", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}, {"key": "dc.type.okm", "value": "G2", "language": null, "element": "type", "qualifier": "okm", "schema": "dc"}]
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