高雄市為台灣的石化工業重鎮，近年來因管線運輸的發達，許多工業區選擇以管線運輸做為運送化學品的方式。但自從2014年摧殘高雄南部地區的管線氣爆事件發生後，高雄居民對於管線運輸的安全性產生疑慮；因此，危險物品運輸的方式逐漸由管線運輸轉換為化學槽車運輸。但槽車的行駛依舊對居民安危造成嚴重影響，因而突顯路線選擇對於危險物品運輸的重要性。
本研究建構一妥協規劃模型，在考量旅行成本、旅行風險以及恢復力下，選擇多種目標下的運輸路線。研究目的之一為以傳統風險模型定義路徑風險，利用風險評估標的，如高雄道路特性、人口分布、路段長度、危險物品特性及意外事故率等，建構出得以衡量路段及路線之風險評估指標。再者，本研究納入恢復力的概念，在危險物品運送過程中，意外是可能發生的，較高的恢復力表示路網有較好的能力得以從意外中恢復；因此路線的恢復力亦為須納入考量之重要議題。在危險物品運輸的議題當中，消防資源的充足與否是決定路網恢復能力的主要因素之一，因此本研究以消防資源作為恢復力的指標。
本研究將此模型在實際的高雄路網上測試，實驗結果顯現出此方法的可行性，並且能應用於不同地區，根據地區特性調整，得出對該地區環境及居民影響最小的危險物品運輸路網給相關單位適當的建議。

In 2014, the Kaohsiung City in Taiwan suffered from the gas pipeline explosions during the midnight, 32 people were killed, and hundreds of people injured. After the incidents, hazmat transportation on roads are initiated to avoid pipeline transportation. In order to fulfill the needs of chemicals, numerous chemical tank cars are needed, but those chemical tank cars travel on road also pose huge dangers to citizens, which highlights the importance of choosing the most appropriate path for hazmat transportation.
The study proposes a compromise weight algorithm for selecting the transportation routes under multi-objectives, including travel cost, travel risk and resilience, and a formulation of the multi-objective route selection problem is developed. One of the purposes of this research is to define risk by traditional risk model. By several risk assessment indexes such as road characteristics, population distribution, link length, hazmat’ characteristics, and accident rate, we establish a risk measurement indicator which could evaluate the risk of each link and route. Furthermore, we put the concept of resilience into this research, during the process of hazmat transportation, accidents may happen, higher resilience represents the network having better capability to recover from the accident. In the field of hazmat transportation, fire service resources is adequate or not is one of the main factors that having impact on network resilience. Hence, we put fire service resources as the index of resilience.
The proposed method is tested in a realistic road network in Kaohsiung, Taiwan. The results of experiments show the feasibility of the proposed algorithm and also propose appropriate advices for relative authorities to construct a hazmat transportation network which having the least impact to the environment and residents. The model is also appropriate for other area and can be adjusted based on the characteristics of the tested area.

1. Abkowitz, M., M. Lepofsky, and P. Cheng. (1992). “Selecting Criteria for Designating Hazardous Materials Highway Routes”. Transp. Res. 1333, 30–35.
2. Abkowitz, M. and Cheng, P. D. M. (1988). “Developing a risk/cost framework for routing truck movements of hazardous materials.” Accident Analysis and Prevention, 20(1), 39-51.
3. Alumur, S. and Kara, B. Y. (2007). “A new model for the hazardous waste location-routing problem.” Computers and Operations Research, 34(5), 1406-1423.
4. Berman, O., Verter, V., and Kara, B. Y. (2007). “Designing emergency response networks for hazardous materials transportation.” Computers and operations research, 34(5), 1374-1388.
5. Bianco, L., Caramia, M., and Giordani, S. (2009). “A bilevel flow model for hazmat transportation network design.” Transportation Research Part C: Emerging Technologies, 17(2), 175-196.
6. Britton, N. R. and Clark, G. J. (2000). “From response to resilience: emergency management reform in New Zealand.” Natural Hazards Review, 1(3), 145-150.
7. Chakrabarti, U. K. and Parikh, J. K. (2013). “Risk-based route evaluation against country-specific criteria of risk tolerability for hazmat transportation through Indian State Highways.” Journal of Loss Prevention in the Process Industries,26(4), 723-736.
8. Cohen M. A. and Lee H. L.,(1998)“ Strategic Analysis of Integrated Production-Distribution Systems：Models and Methods”, Operations Research,36(2), pp.216-228
9. Current, J. and Ratick, S. (1995). “A model to assess risk, equity and efficiency in facility location and transportation of hazardous materials.” Location Science,3(3), 187-201.
10. Deb, K. (2001). “Multi-objective optimization using evolutionary algorithms” (Vol. 16). John Wiley and Sons.
11. Deb, K. (2011), “Multi-Objective Optimization Using Evolutionary Algorithms: An Introduction,” KanGAL Report No.2011003.
12. Erkut, E. and Verter, V. (1995). “A framework for hazardous materials transport risk assessment.” Risk Analysis, 15(5), 589-601.
13. Erkut, E. and Verter, V. (1998). “Modeling of transport risk for hazardous materials. Operations research”, 46(5), 625-642.
14. Giannikos, I. (1998). “A multiobjective programming model for locating treatment sites and routing hazardous wastes.” European Journal of Operational Research, 104(2), 333-342.
15. Godschalk, D. R. (2003). “Urban hazard mitigation: Creating resilient cities,” Natural Hazards Review, 4(3), 136-143.
16. Harwood, D. W., Viner, J. G., and Russell, E. R. (1993). “Procedure for developing truck accident and release rates for hazmat routing,” Journal of transportation engineering, 119(2), 189-199.
17. Holling, C. S. (1973). “Resilience and stability of ecological systems,” Annual Review of Ecology and Systematics, 4, 1-23.
18. Huang, B., Cheu, R. L., and Liew, Y. S. (2004). “GIS and genetic algorithms for HAZMAT route planning with security considerations.” International Journal of Geographical Information Science, 18(8), 769-787
19. Kang, Y., Batta, R., and Kwon, C. (2014). “Generalized route planning model for hazardous material transportation with var and equity considerations.” Computers and Operations Research, 43, 237-247.
20. Kao, C. and Hung, H. T. (2005). “Data envelopment analysis with common weights: the compromise solution approach.” Journal of the Operational Research Society, 56(10), 1196-1203.
21. List, G. F., Mirchandani, P. B., Turnquist, M. A., and Zografos, K. G. (1991). “Modeling and analysis for hazardous materials transportation: Risk analysis, routing/scheduling and facility location.” Transportation Science, 25(2), 100-114.
22. Li, R. and Leung, Y. (2011). “Multi-objective route planning for dangerous goods using compromise programming.” Journal of geographical systems, 13(3), 249-271.
23. Li, R., Leung, Y., Huang, B., and Lin, H. (2013). “A genetic algorithm for multiobjective dangerous goods route planning”. International Journal of Geographical Information Science, 27(6), 1073-1089
24. Li, X. and Jiang, H. (2013). “Optimization for hazardous materials road transportation based on multi-objective method.” In Proceedings of the 2013 Third International Conference on Intelligent System Design and Engineering Applications (pp. 1034-1037). IEEE Computer Society.
25. Murray-Tuite, P. M. (2006). “A comparison of transportation network resilience under simulated system optimum and user equilibrium conditions,” Simulation Conference, 2006. WSC 06. Proceedings of the Winter, 1398-1405.
26. Pradhananga, R., Taniguchi, E., and Yamada, T. (2010). “Ant colony system based routing and scheduling for hazardous material transportation.” Procedia-Social and Behavioral Sciences, 2(3), 6097-6108.
27. United Nations, "Recommendations on the Transport of Dangerous Goods,” 17th ed., New York and Geneva, 2011.
28. Reggiani, A. (2012). “Network resilience for transport security: Some methodological considerations,” Transport Policy, 28, 63-68.
29. Tamvakis, P. and Xenidis, Y. (2012). “Resilience in transportation systems,” Procedia-Social and Behavioral Sciences, 48, 3441-3450.
30. Tierney, K. and Bruneau, M. (2007). “Conceptualizing and measuring resilience: A key to disaster loss reduction.” TR news, (250).
31. Zografos, K. G. and Androutsopoulos, K. N. (2004). “A heuristic algorithm for solving hazardous materials distribution problems.” European Journal of Operational Research, 152(2), 507-519.
32. 洪僖黛. (2005). 妥協權重資料包絡分析模式之求解與應用. 成功大學工業與資訊管理學系學位論文, 1-103.
33. 陳一昌(2011)，「道路危險物品運送風險評估機制之規劃研究」，交通部運輸研究所，民國100年。
34. 張新立(1990)，「台灣地區危險物品道路運輸路線風險評估模式之研究」，運輸計畫季刊，第十九卷第四期p389-p408，民國79年。
35. 張承明等(2005)，「危險物品運輸之事故危害分析-引火性液體」，行政院勞工委員會勞工安全衛生研究所，民國94年。
36. 高雄市消防統計年報(2014)，高雄市政府消防局。
37. 國道事故檢討分析報告(2014)，交通部國道高速公路局。
38. 統計年報(2014)，交通部國道高速公路局。
39. 統計年報(2014)，交通部公路總局。
40. 統計年報(2014)，內政部警政署。
41. 里別人口統計 (2014)，高雄市政府民政局。
42. 各里面積統計，高雄市政府民政局。