دانلود مقاله ISI انگلیسی شماره 43713
ترجمه فارسی عنوان مقاله

روش بهینه سازی شبیه سازی برای کامیون داخلی با اشتراک گذاری تخصیص میان پایانه های کانتینری متعدد

عنوان انگلیسی
A simulation optimization method for internal trucks sharing assignment among multiple container terminals
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
43713 2013 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Advanced Engineering Informatics, Volume 27, Issue 4, October 2013, Pages 598–614

ترجمه کلمات کلیدی
پایانه های کانتینری متعدد - برنامه ریزی کامیون داخلی - استراتژی به اشتراک گذاری - برنامه ریزی عدد صحیح - بهینه سازی شبیه سازی
کلمات کلیدی انگلیسی
Multiple container terminals; Internal trucks scheduling; Sharing strategy; Integer programming; Simulation optimization
پیش نمایش مقاله
پیش نمایش مقاله  روش بهینه سازی شبیه سازی برای کامیون داخلی با اشتراک گذاری تخصیص میان پایانه های کانتینری متعدد

چکیده انگلیسی

Owing that the internal trucks (ITs) are frequently used as transportation equipments between yards and quaysides, the transportation efficiency of ITs secures a crucial position in container terminal productivity. Hence, a container terminal cannot contain a big number of ITs. As such, it is an imperative to explore an appropriate IT assignment strategy. Specifically for those container terminals with adjacent locations, an approach to sharing internal trucks among multiple container terminals (SIMT) is investigated. In this study, a novel strategy to resolve the SIMT problem was proposed for a specific large port with multiple adjacent container terminals. Firstly, an illustration of the SIMT strategy was presented. Then, an integer programming model for this problem is developed, where the objective functions are subject to the minimization of the total overflowed workloads and total transferring costs in every time-period among these container terminals. In particular, the rolling-horizon approach is employed for considering the immediate scheduling. Furthermore, a simulation optimization method, which integrates the genetic algorithm (GA) searching and simulation, is proposed for the near optimal solutions. Finally, the computational experiments are used to verify the effectiveness of the proposed SIMT strategy and simulation optimization method.