Reverse Logistics Management Based on the Ant Colony Optimization - A Case Study on Hospital Waste in Indonesia
碩士 === 國立臺灣科技大學 === 工業管理系 === 102 === The waste management is one of important processes to manage wastes to avoid contaminating the surrounding neighborhood. Two main activities in managing wastes is collecting and transporting wastes from the place which produced them to final disposal place calle...
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| Format: | Others |
| Language: | en_US |
| Published: |
2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/26451363775803491627 |
| Summary: | 碩士 === 國立臺灣科技大學 === 工業管理系 === 102 === The waste management is one of important processes to manage wastes to avoid contaminating the surrounding neighborhood. Two main activities in managing wastes is collecting and transporting wastes from the place which produced them to final disposal place called dumping place. These kind of activities need effective and efficient way to be implemented especially in finding the minimum distance from each source of wastes to the final disposal place so it will minimize the cost in the waste management system. Finding minimum distance can be associated as the Vehicle Routing Problem (VRP). In the case of collecting and transporting the wastes, the type of VRP used is called the Capacitated Vehicle Routing Problem (CVRP) because it involves capacity constraint between the amount of wastes of each place and the vehicle used to pick up the wastes. This thesis is based on real case in Jakarta, Indonesia which focuses on the CVRP in picking up and transporting wastes from the hospitals to the landfill as final disposal place.
The hybrid method combining the sweep method and the Ant Colony Optimization (ACO) method is proposed to find the optimal solutions of minimum distance in picking up wastes from the hospitals to the landfill. Comparisons are made between the proposed hybrid method and the Genetic Algorithm (GA) to test that our algorithm is reliable to solve the problem. Experiment results show that the proposed hybrid method was able to find the optimal solution better than the GA for all 30 benchmark problems and also for the real case involving the hospitals in Jakarta, Indonesia. The hybrid method is also robust and competitive over the GA.
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