کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1133990 1489096 2014 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A hybrid constructive heuristic and simulated annealing for railway crew scheduling
ترجمه فارسی عنوان
یک هیبرید سازنده هلیکوپتر اکتشافی و شبیه سازی شده برای برنامه ریزی خدمه راه آهن
کلمات کلیدی
برنامه ریزی خدمه راه آهن، برنامه ریزی ریاضی، اکتشافات ساختاری، شبیه سازی شده، بهینه سازی ترکیبی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی صنعتی و تولید
چکیده انگلیسی


• A mathematical model and algorithms are developed for railway crew scheduling.
• The number of crew duties is minimised by reducing the total idle transition times.
• The interval of relief opportunities is included into the model and algorithms.
• A hybrid constructive heuristic and SA metaheuristic is applied to solve the problem.
• Near-optimal crew schedules are obtained within an acceptable cpu time.

Railway crew scheduling problem is the process of allocating train services to the crew duties based on the published train timetable while satisfying operational and contractual requirements. The problem is restricted by many constraints and it belongs to the class of NP-hard. In this paper, we develop a mathematical model for railway crew scheduling with the aim of minimising the number of crew duties by reducing idle transition times. Duties are generated by arranging scheduled trips over a set of duties and sequentially ordering the set of trips within each of duties. The optimisation model includes the time period of relief opportunities within which a train crew can be relieved at any relief point. Existing models and algorithms usually only consider relieving a crew at the beginning of the interval of relief opportunities which may be impractical. This model involves a large number of decision variables and constraints, and therefore a hybrid constructive heuristic with the simulated annealing search algorithm is applied to yield an optimal or near-optimal schedule. The performance of the proposed algorithms is evaluated by applying computational experiments on randomly generated test instances. The results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time for large-sized problems.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Industrial Engineering - Volume 70, April 2014, Pages 11–19
نویسندگان
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