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Instance space analysis for the generalized bin packing problem algorithms
Instance space analysis for the generalized bin packing problem algorithms In the generalised bin packing problem, the objective is to pack a selected set of profitable non-compulsory items with all the compulsory ones into a set of bins such that the resulting packing cost is minimised. The total c...
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| Format: | Thesis |
| Language: | English English |
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Department of Statistical Sciences
2026
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| _version_ | 1867613172760838144 |
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| access_status_str | Open Access |
| author | Netshitungulu, Funanani |
| author2 | Rakotonirainy, Rosephine Georgina |
| author_browse | Netshitungulu, Funanani Rakotonirainy, Rosephine Georgina |
| author_facet | Rakotonirainy, Rosephine Georgina Netshitungulu, Funanani |
| author_sort | Netshitungulu, Funanani |
| collection | Thesis |
| description | Instance space analysis for the generalized bin packing problem algorithms In the generalised bin packing problem, the objective is to pack a selected set of profitable non-compulsory items with all the compulsory ones into a set of bins such that the resulting packing cost is minimised. The total cost is given by the difference between the cost of the selected bins and the total profit of the loaded items. This type of problem is encountered in logistics, mainly in the transportation industry which has grown massively over the years. In this thesis, six improved heuristics are proposed to tackle this problem. The aim is to investigate the upper bound solutions provided by such heuristic approaches to the problem. An Instance Space Analysis is also applied to test the efficiency and effectiveness of the algorithms in respect of the problem instance space. In particular, the relationship between the problem instance features and the algorithm performance is studied. The results indicate that the chosen features are able to explain the difficulty of the problem instances, highlighting the strengths and weaknesses of the various algorithms. This work contributes to the advancement of research in the context of packing problem instance space analysis. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/42542 |
| institution | University of Cape Town (South Africa) |
| language | English eng |
| last_indexed | 2026-06-10T12:31:54.917Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/42542 Instance space analysis for the generalized bin packing problem algorithms Netshitungulu, Funanani Rakotonirainy, Rosephine Georgina Instance space analysis Instance space analysis for the generalized bin packing problem algorithms In the generalised bin packing problem, the objective is to pack a selected set of profitable non-compulsory items with all the compulsory ones into a set of bins such that the resulting packing cost is minimised. The total cost is given by the difference between the cost of the selected bins and the total profit of the loaded items. This type of problem is encountered in logistics, mainly in the transportation industry which has grown massively over the years. In this thesis, six improved heuristics are proposed to tackle this problem. The aim is to investigate the upper bound solutions provided by such heuristic approaches to the problem. An Instance Space Analysis is also applied to test the efficiency and effectiveness of the algorithms in respect of the problem instance space. In particular, the relationship between the problem instance features and the algorithm performance is studied. The results indicate that the chosen features are able to explain the difficulty of the problem instances, highlighting the strengths and weaknesses of the various algorithms. This work contributes to the advancement of research in the context of packing problem instance space analysis. 2026-01-13T07:12:25Z 2026-01-13T07:12:25Z 2025 2026-01-12T07:13:32Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/42542 en eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Instance space analysis Netshitungulu, Funanani Instance space analysis for the generalized bin packing problem algorithms |
| thesis_degree_str | Master's |
| title | Instance space analysis for the generalized bin packing problem algorithms |
| title_full | Instance space analysis for the generalized bin packing problem algorithms |
| title_fullStr | Instance space analysis for the generalized bin packing problem algorithms |
| title_full_unstemmed | Instance space analysis for the generalized bin packing problem algorithms |
| title_short | Instance space analysis for the generalized bin packing problem algorithms |
| title_sort | instance space analysis for the generalized bin packing problem algorithms |
| topic | Instance space analysis |
| url | http://hdl.handle.net/11427/42542 |
| work_keys_str_mv | AT netshitungulufunanani instancespaceanalysisforthegeneralizedbinpackingproblemalgorithms |