Model and solutions to campus parking space allocation problem.
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Date
2013
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Abstract
Parking 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.
Description
M. Sc. University of KwaZulu-Natal, Durban 2013.
Keywords
University of KwaZulu-Natal--Parking., Campus parking--South Africa--Durban., Combinatorial optimization., Heuristic algorithms., Parking facilities., Theses--Computer science.