دانلود مقاله ISI انگلیسی شماره 22796
ترجمه فارسی عنوان مقاله

یک نکته در "سیستم مورچه ای حداکثر-حداقل برای مشکلات تعیین اندازه دسته تولید نامحدود چند سطی"

عنوان انگلیسی
A Note on “A MAX-MIN Ant System for Unconstrained Multi-Level Lot-Sizing Problems”
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
22796 2012 5 صفحه PDF
منبع

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

Journal : Procedia Engineering, Volume 29, 2012, Pages 1137–1141

ترجمه کلمات کلیدی
تعیین اندازه دسته تولید چند سطحی - سیستم مورچه ها - نیاز برنامه ریزی مواد مورد -
کلمات کلیدی انگلیسی
Multilevel lot-sizing, RCWW, ant systems, material requirements planning, metaheuristic,
پیش نمایش مقاله
پیش نمایش مقاله  یک نکته در "سیستم مورچه ای حداکثر-حداقل برای مشکلات تعیین اندازه دسته تولید نامحدود چند سطی"

چکیده انگلیسی

Pitakaso et al.[1] presented an ant systems based on random cumulative Wagner-Whitin (RCWW) (RCWW-STVS) for uncapacitated multilevel lot-sizing (MLLS) problems and gave out a computational result for Dellaert's instance [2] with a random variable r = 0.43. The result is not quite right. This paper highlighted the error and presented a revision to the result.

مقدمه انگلیسی

Pitakaso et al. [1] presented a RCWW-STVS algorithm to solve multilevel lot-sizing problems without resource constraints. To prove their algorithm is superior to Dellaert et al. [2]’s RCWW algorithm, they presented a result reached by RCWW-STVS algorithm for reference [2]’s instance with product order of {2, 5, 1, 3, 4, 6, 8, 7, 9}, setup cost accumulative parameters ri ={0.43, 0.43, 0.43, 0.43, 0.43, 0.43, 0.43, 0.43, 0.43} and the inventory costs for material 1 to 9 is {13, 8, 4, 4, 3, 3, 2, 1, 1}. The product structure is shown in Fig.1. The underlined number is lead time for each material and the right side number is setup cost for each material. The inner demand relation between materials is 1 to 1. The result from [1] is presented in Table 1. There are no errors for parameters but the result for reference [2]’s instance. Here we note in Table 1, the demand for material 1 is {0, 0, 0, 0, 10, 15, 10, 12, 20}. Material 1’s production lot, according to [1], is {0, 0, 0, 0, 10, 15, 10, 12, 20}. Then for material 3, taking into consideration of material 1’s lead time, the demand is {0, 0, 0, 10, 15, 10, 12, 20, 0}. As we seen from Table 1, the revised setup cost of material 3 is {0, 0, 0, 41.5, 30, 30, 30, 30, 30}. The production lot of material 3 reached by [1] is {0, 0, 0, 10, 25, 0, 12, 20, 0}. However, we can find that the setup cost in period 6 of material 3 is 30 and the inventory cost in period 5 of material 3 is 4. If producing 10 products in period 6, the cost is 30. However, according to Pitakaso et al.[1]’s result, 10 units of material 3 are kept in inventory for 1 period. Then the cost is 10*4=40. So we can easily tell a production decision {0, 0, 0, 10, 15, 10, 12, 20, 0} is better than another one {0, 0, 0, 10, 25, 0, 12, 20, 0}. After a practical verification with C program language, we got a result, which is a revision to reference [1]’s result, for Dellaert et al.[2]’s instance and presented it in Table 2. The material presentation of MLLS problem is shown in Fig.2. Fig.3 shows the output interface of VC++ program.

نتیجه گیری انگلیسی

In this paper, we pointed out an error in literature [2] and gave out the revision for this error. The significance of this paper is twofold: 1) the reason why Pitakaso et al.[1]’s algorithm have produced questionable results is pointed out; 2) all those results from reference [1] are not fully optimized.