Determining tactical operations policies for an auto carrier using discrete-event simulation
| dc.contributor.advisor | Bekker, James F. | en_ZA |
| dc.contributor.author | Du Plessis, Annemie J. | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. | |
| dc.date.accessioned | 2008-11-27T08:42:10Z | en_ZA |
| dc.date.accessioned | 2010-06-01T08:55:07Z | |
| dc.date.available | 2008-11-27T08:42:10Z | en_ZA |
| dc.date.available | 2010-06-01T08:55:07Z | |
| dc.date.issued | 2008-12 | |
| dc.description | Thesis (MScEng (Industrial Engineering))--Stellenbosch University, 2008. | |
| dc.description.abstract | Passenger cars are either imported to or assembled in South Africa, and then distributed to the customer. An important part of the supply chain is formed by the auto carrier companies who do this distribution. The basis of this thesis is a study that was executed in collaboration with a South African auto carrier company, and the objective was to improve the long-distance auto carrier fleet management through improved tactical operational policies. These policies focus on application of the fleet by assigning transportation vehicles to routes, as well as the business rules that must be followed at pick-up and drop-off locations. Several rules were developed during this study, which, together with specific transportation vehicle (carriers) assignments, form operational scenarios. The quality of each scenario was evaluated using discrete event simulation over a six month time-span, and considering four decision parameters simultaneously. These parameters are 1) useful kilometres travelled by the long-distance carriers, 2) empty kilometres travelled by the same long-distance carriers, 3) the expected number of cars waiting to be transported and 4) the expected time it takes to deliver a car to its destination. A high level of uncertainty prevails in these transportation operations, while fluctuating demand calls for the dynamic allocation and management of carriers in order to sustain an acceptable service level in a cost-effective manner. The best tactical policies should maximize the number of cars delivered on time at the lowest cost. Major constraints considered are staff- and maintenance schedules. While searching for the best of several scenarios, multiple, conflicting criteria had to be evaluated, as mentioned above. Two multi-criteria decision analysis (MCDA) methods were used namely SAW and TOPSIS, while the Mahalanobis distance method was also applied as an evaluation technique. These methods were used to rank scenarios. Additionally, the application of Portfolio theory and the efficient frontier was investigated for applicability to the problem studied. An analogy to the efficient frontier providing an additional means for scenario selection and evaluation was developed. The result of this study provides the decision maker of the auto carrier company with a tactical decision aid, consisting of the MCDA and Mahalanobis scenario rankings, a cost-benefit graph and a fleet portfolio efficient frontier, to aid long-distance carrier management. Additionally, a sensitivity analysis was also done for strategic planning concerned with the sufficient long-distance carrier fleet size. The first part of this thesis comprises a study of literature in which freight operations, auto carrier studies and the auto carrier context in South Africa are investigated. The problem is formulated and a suitable formulation and solution tool identified. Multi-criteria decision analysis is also investigated in order to enable scenario evaluation. The solution development phase consisted of the simulation model concept development, acquisition of input data, model verification and validation, scenario construction, simulation execution, and analysis of results. | en |
| dc.identifier.uri | http://hdl.handle.net/10019.1/2676 | |
| dc.language.iso | en | |
| dc.publisher | Stellenbosch : Stellenbosch University | |
| dc.rights.holder | Stellenbosch University | |
| dc.subject | Simulation | en |
| dc.subject | Freight transportation | en |
| dc.subject | Multi-attribute decision making | en |
| dc.subject | Auto carriers | en |
| dc.subject | Dissertations -- Industrial engineering | en |
| dc.subject | Theses -- Industrial engineering | en |
| dc.title | Determining tactical operations policies for an auto carrier using discrete-event simulation | en |
| dc.type | Thesis |
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