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dc.contributor.advisorAdewumi, Aderemi Oluyinka.
dc.creatorJoel, Luke Oluwaseye.
dc.date.accessioned2015-01-05T07:37:06Z
dc.date.available2015-01-05T07:37:06Z
dc.date.created2013
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10413/11810
dc.descriptionM. Sc. University of KwaZulu-Natal, Durban 2013.en
dc.description.abstractParking is considered a major land use challenge in campus planning. The problem can be in terms of scarcity (few available spaces compared to demand) or management (ineffi cient usage of available facilities). Many studies have looked at the parking problem from the administrative and management points of view. However, it is believed that mathematical models and optimiza- tion can provide substantial solution to the parking problem. This study investigates a model for allocating car parking spaces in the university environment and improves on the constraints to address the reserved parking policy on campus. An investigation of both the exact and heuristic techniques was undergone to provide solutions to this model with a case study of the University of KwaZulu-Natal (UKZN), Westville Campus. The optimization model was tested with four different set of data that were generated to mimic real life situations of parking supply and demand on campus for reserved and unreserved parking spaces. These datasets consist of the number of parking lots and offi ce buildings in the case study. The study also investigate some optimization algorithms that can be used to obtain solutions to this problem. An exact solution of the model was generated with CPLEX solver (as incorporated in AIMMS software). Further investigation of the performance of the three meta-heuristics to solve this problem was done. A comparative study of the performance of these techniques was conducted. Results obtained from the meta-heuristic algorithms indicate that the algorithms used can successfully solve the parking allocation problem and can give solutions that are near optimal. The parking allocation and fitness value for each of the meta-heuristic algorithms on the sets of data used were obtained and compared to each other and also to the ones obtained from CPLEX solver. The results suggest that PSwarm performs better and faster than the other two algorithms and gives solutions that are close to the exact solutions obtained from CPLEX solver.en
dc.language.isoen_ZAen
dc.subjectUniversity of KwaZulu-Natal--Parking.en
dc.subjectCampus parking--KwaZulu-Natal--Durban.en
dc.subjectCombinatorial optimization.en
dc.subjectHeuristic algorithms.en
dc.subjectParking facilities.en
dc.subjectTheses--Computer science.en
dc.titleModel and solutions to campus parking space allocation problem.en
dc.typeThesisen


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