| 摘要: | 良好的捷運車廂檢修人力供給規劃，可幫助捷運檢修工廠有效率地完成檢修工作，以確保捷運車廂的行駛安全與維持良好的服務品質。目前檢修工廠大多以預測的平均人力需求值，以人工經驗進行人力的供給規劃。然而此作法忽略了實務營運上，每日人力需求的隨機變動情形，若此隨機性過大，則可能使原規劃的人力供給及班次表失去其最佳性。另外，目前檢修工廠以固定執勤班次與固定工作時數的方式，進行人力的供給規劃，此作法不但缺乏彈性，亦可能導致人力供給無法與實際的檢修需求配合，造成供需不均衡的現象。有鑑於此，為能反映真實之需求狀況與提升人力的有效運用，本研究以捷運檢修工廠之立場，考量實際營運時人力需求之隨機變動及人力資源的彈性策略，針對長期規劃與短期規劃上不同之限制條件，各自發展數個確定性與隨機/混合需求之人力供給排班模式。本研究模式期能於未來實務的應用上，提供捷運檢修工廠在隨機環境中，規劃最佳的人力供給及班次表。 本研究構建數個確定性需求排班模式，並進一步修正確定性需求排班模式中之固定需求值為隨機需求值，建立數個隨機/混合需求排班模式。以上模式皆可定式為混合整數規劃問題，屬NP-hard問題。在求解上，確定性需求模式本研究發展以鬆弛整數限制為基礎之啟發解法，而針對隨機與混合需求模式，則利用線性分解技巧、模擬技巧、並結合CPLEX發展啟發解法，以有效的求解模式。為評估隨機性需求排班模式與啟發解法所求得的人力供給規劃班次表於隨機環境中營運的績效，本研究發展一模擬評估方法。最後，為測試本研究模式與解法的實用績效，本研究以國內一捷運檢修工廠之為例，進行範例測試與分析，結果甚佳，顯示本研究所構建之模式與求解方法應可為未來實務捷運車廂維修單位之參考。 A good carriage maintenance manpower supply plan helps Mass Rapid Transit (MRT) plants efficiently deal with their maintenance and improve their service quality. To design a good carriage maintenance manpower supply plan, a plant has to consider not only its operating cost, but also the uncertainty of the daily manpower demand in actual operations. However, currently the carriage maintenance in Taiwan depends on staff experience with a fixed demand in establishing the manpower supply plan, which is neither effective nor efficient. In the worst case scenario, the manpower demands for continuous time slots fluctuate drastically (e.g., on the boundaries of peak and off-peak periods), then supplying too much manpower to meet the highest demand would result in too much surplus manpower and a waste of human resources. Hence, in this research we develop for the MRT maintenance plants several deterministic-demand, stochastic-demand and mixed deterministic and stochastic demand manpower supply plan models for their long-term and short-term operations. The models are expected to be useful planning tools for the MRT maintenance plants to decide on their optimal manpower supply plans and timetables in their operations. We employed mathematical programming techniques, incorporating the flexible manpower supply strategies, to construct several deterministic-demand scheduling models. Then, we further developed several stochastic-demand and mixed deterministic and stochastic demand manpower supply plan models by modifying the fixed demand parameters in the corresponding deterministic-demand manpower supply plan models. These models are formulated as mixed integer programs that are characterized as NP-hard. For ease of testing, we developed heuristics based on relaxing integer restriction in the deterministic-demand scheduling models. With regard to stochastic-demand and mixed demands scheduling models, we employed linear decomposition techniques, simulation techniques, coupled with CPLEX, to develop heuristics to efficiently solve the problems. To evaluate the models and the solution algorithms under stochastic demands in actual operations, we developed a simulation-based evaluation method. Finally, we performed a case study using real operating data from a Taiwan MRT maintenance plant. The preliminary results are good, showing that the models could be useful for planning carriage maintenance manpower supply. |
