دانلود رایگان مقاله لاتین حداقل سازی bin packing از سایت الزویر


عنوان فارسی مقاله:

حداقل سازی حداکثر تاخیر در bin packing تک بعدی


عنوان انگلیسی مقاله:

Maximum lateness minimization in one-dimensional bin packing


سال انتشار : 2017



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بخشی از مقاله انگلیسی:


3. Use of bounds 

A careful use of bounds in formulations ðkxÞ and ðgxÞ definitely improves their performance. Dual (i.e., lower) and primal (i.e., upper) bounds to the objective function play a well-known role in pruning the search tree during branch-and-bound and reducing optimality gaps. But separate bounds to the terms that form the objective function are also very useful. On the one hand, upper bounds to Cmax can help reduce T and hence the number of time-indexed variables in both ðkxÞ and ðgxÞ. On the other hand, lower bounds to Lmax can be fruitfully employed to fix variables xjt of ðkxÞ through constraints (5); improve the dual LP bound of ðgxÞ through the reduction of the “big M” f 2 j ðtÞ in the third set of inequalities. Fig. 1 shows a schematic drawing of the objective function space Cmax vs. Lmax. Appealing values belong to the dark grey triangle: the combination of bounds to the two terms and to the objective function as a whole allow to infer new (and possibly stronger) specific bounds to each term. 3.1. Lower bounds If CLB; LLB are individual lower bounds to Cmax; Lmax, then zLB ¼ α1⌈CLB⌉þα2⌈LLB⌉ is indeed a lower bound to (1) – notice that round up of LLB is authorized by Assumption 1.1 (ii) (integer due dates). We can prove the following: Proposition 3.1. Let CLB be any lower bound to Cmax, and Fn be the value of a schedule that minimizes F ¼ maxff jðCjÞg. If the fj are F regular, then α1⌈CLB⌉þα2Fn is a lower bound to f ¼ α1Cmax þα2F. Proof. Under regularity, Fn is in fact a lower bound to the value of F attained by a minimizer of f, see [2].



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کلمات کلیدی:

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