کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1032388 1483665 2016 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
New heuristics for the Stochastic Tactical Railway Maintenance Problem
ترجمه فارسی عنوان
فن آوری هوشمند جدید برای مسئله تعمیر و نگهداری تاکتیکی تصادفی راه آهن
کلمات کلیدی
تعمیر و نگهداری راه آهن؛ ابتکارات؛ روش جستجو تطبیقی تصادفی؛ الگوریتم ژنتیک
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری استراتژی و مدیریت استراتژیک
چکیده انگلیسی


• We considered the Stochastic Tactical Railway Maintenance Problem (STRMP).
• We exploited the analogies of the STRMP with a number of bin packing problems.
• We proposed a model for the deterministic subproblem and three efficient heuristics able to effectively address the stochastic problem.

Efficient methods have been proposed in the literature for the management of a set of railway maintenance operations. However, these methods consider maintenance operations as deterministic and known a priori. In the Stochastic Tactical Railway Maintenance Problem (STRMP), maintenance operations are not known in advance. In fact, since future track conditions can only be predicted, maintenance operations become stochastic. The STRMP is based on a rolling horizon. For each month of the rolling horizon, an adaptive plan must be addressed. Each adaptive plan becomes deterministic, since it consists of a particular subproblem of the whole STRMP. Nevertheless, an exact resolution of each plan along the rolling horizon would be too time-consuming. Therefore, a heuristic approach that can provide efficient solutions within a reasonable computational time is required. Although the STRMP has already been introduced in the literature, little work has been done in terms of solution methods and computational results. The main contributions of this paper include new methodology developments, a linear model for the deterministic subproblem, three efficient heuristics for the fast and effective resolution of each deterministic subproblem, and extensive computational results.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Omega - Volume 63, September 2016, Pages 94–102
نویسندگان
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