Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems /
Optimization is a major challenge in numerous practical world problems. According to the “No Free Lunch (NFL)” theorem, there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner. It is varied and need to be solved according to the specifi...
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| Формат: | Програмне забезпечення eКнига |
| Мова: | English |
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2018.
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| 100 | 0 | |a Nur Farraliza Mansor, |e author. |9 2726 | |
| 245 | 1 | 0 | |a Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems / |c Nur Farraliza Mansor. |
| 264 | 1 | |c 2018. | |
| 300 | |a xiv, 256 pages : |b some colour illustrations, charts ; |c 30 cm + |e 1 computer disc (12 cm ) | ||
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| 347 | |a text file |b PDF |c 2.97 MB |2 rda | ||
| 500 | |a Accompanied by CD : CDR 18235. | ||
| 504 | |a Reference : pages 238-256. | ||
| 520 | |a Optimization is a major challenge in numerous practical world problems. According to the “No Free Lunch (NFL)” theorem, there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner. It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem. As a result, the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm. Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort. However, the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases; therefore a type of nature-inspired algorithm known as meta-heuristics which utilises an intelligent searching mechanism over a population is considered and consequently used. The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling. However, this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems. Hence, this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering. The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems. In this respect, the three main operators in harmony search, namely the Harmony Memory Consideration Rate (HMCR), Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration. These parameters influence the overall performance of the HS algorithm, and therefore it is crucial to fine-tune them. Therefore, it is of great interest that we find adjustments for these parameters in this research. There are two contributions to this research. The first one is having HMCR parameter using step function and the linear increase function while the second is applying the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter. There are three proposed models on the alteration of HMCR parameters based on the use of the fundamental step function; namely, the constant interval of step function, and its dynamic increase and decrease interval functions. The experimental results revealed that our proposed approach is superior to other state of the art harmony searches either in specific or generic cases. This is achieved by using a first type of association between the linear increase function with a second model of the dynamic increase of step function being remarkable in other combinations and also other models. In conclusion, this proposed approach managed to generate a fairer roster and was thus capable of maximising the balancing distribution of shifts and routes among drivers, which contributed to the lowering of illness, incidents, absenteeism and accidents. | ||
| 650 | 0 | |a Algorithms |x Data processing. |9 4496 | |
| 650 | 0 | |a Harmonic analysis. |9 4497 | |
| 710 | 2 | |a Universiti Teknikal Malaysia Melaka, |e issuing body. |9 2727 | |
| 720 | |a Associate Professor Dr. Zuraida Abal Abas | ||
| 790 | |a Faculty of Information and Communication Technology | ||
| 791 | |a Doctor of Philosophy | ||
| 792 | |a 2018 | ||
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