In this paper we study the scheduling problem in which each customer order consists of several jobs of different types, which are to be processed on m facilities. Each facility is dedicated to the processing of only o...
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In this paper we study the scheduling problem in which each customer order consists of several jobs of different types, which are to be processed on m facilities. Each facility is dedicated to the processing of only one type of jobs. All jobs of an order have to be delivered to the customer at the same time. The objective is to schedule all the orders to minimize the total weighted order completion time. While the problem has been shown to be unary NP-hard, we develop a heuristics to tackle the problem and analyze its worst-case performance. (c) 2005 Published by Elsevier Ltd.
We present improved approximation algorithms for directed multicut and directed sparsest cut. The current best known approximation ratio for these problems is O(n(1/2)). We obtain an (O) over tilde (n(11/23))-approxim...
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ISBN:
(纸本)9781595936318
We present improved approximation algorithms for directed multicut and directed sparsest cut. The current best known approximation ratio for these problems is O(n(1/2)). We obtain an (O) over tilde (n(11/23))-approximation. Our algorithm works with the natural LP relaxation used in prior work. We use a randomized rounding algorithm with a more sophisticated charging scheme and analysis to obtain Our improvement. This also implies a (O) over tilde (n(11/23)) upper bound on the ratio between the maximum multicommodity flow kind minimum multicut in directed graphs.
作者:
Zhang, JiaweiNYU
Stern Sch Business IOMS Operat Management New York NY 10012 USA
We propose a quasi-greedy algorithm for approximating the classical uncapacitated 2-level facility location problem (2-LFLP). Our algorithm, unlike the standard greedy algorithm, selects a sub-optimal candidate at eac...
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We propose a quasi-greedy algorithm for approximating the classical uncapacitated 2-level facility location problem (2-LFLP). Our algorithm, unlike the standard greedy algorithm, selects a sub-optimal candidate at each step. It also relates the minimization 2-LFLP problem, in an interesting way, to the maximization version of the single level facility location problem. Another feature of our algorithm is that it combines the technique of randomized rounding with that of dual fitting. This new approach enables us to approximate the metric 2-LFLP in polynomial time with a ratio of 1.77, a significant improvement on the previously known approximation ratios. Moreover, our approach results in a local improvement procedure for the 2-LFLP, which is useful in improving the approximation guarantees for several other multi-level facility location problems. An additional result of our approach is an O(ln (n))-approximation algorithm for the non-metric 2-LFLP, where n is the number of clients. This is the first non-trivial approximation for a non-metric multi-level facility location problem.
An important class of scheduling problems concerns parallel machines and precedence constraints. We consider precedence delays, which associate with each precedence constraint a certain amount of time that must elapse...
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An important class of scheduling problems concerns parallel machines and precedence constraints. We consider precedence delays, which associate with each precedence constraint a certain amount of time that must elapse between the completion and start times of the corresponding jobs. Together with ordinary precedence constraints, release dates and delivery times can be modeled in this manner. We present a 4-approximation algorithm for the total weighted completion time objective for this general class of problems. The algorithm is a rather simple form of list scheduling. The list is in order of job midpoints derived from a linear programming relaxation. Our analysis unifies and simplifies that of a number of special cases heretofore separately studied, while actually improving many of the former approximation results.
作者:
Zhang, JiaweiNYU
Stern Sch Business IOMS Operat Management New York NY 10012 USA
We propose a quasi-greedy algorithm for approximating the classical uncapacitated 2-level facility location problem (2-LFLP). Our algorithm, unlike the standard greedy algorithm, selects a sub-optimal candidate at eac...
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We propose a quasi-greedy algorithm for approximating the classical uncapacitated 2-level facility location problem (2-LFLP). Our algorithm, unlike the standard greedy algorithm, selects a sub-optimal candidate at each step. It also relates the minimization 2-LFLP problem, in an interesting way, to the maximization version of the single level facility location problem. Another feature of our algorithm is that it combines the technique of randomized rounding with that of dual fitting. This new approach enables us to approximate the metric 2-LFLP in polynomial time with a ratio of 1.77, a significant improvement on the previously known approximation ratios. Moreover, our approach results in a local improvement procedure for the 2-LFLP, which is useful in improving the approximation guarantees for several other multi-level facility location problems. An additional result of our approach is an O(ln (n))-approximation algorithm for the non-metric 2-LFLP, where n is the number of clients. This is the first non-trivial approximation for a non-metric multi-level facility location problem.
This paper presents a novel solution methodology for general integer programs using a neighborhood search based on linear programming relaxation. The algorithm generates multiple linearprogramming solutions of maxima...
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ISBN:
(纸本)9789806560710
This paper presents a novel solution methodology for general integer programs using a neighborhood search based on linear programming relaxation. The algorithm generates multiple linearprogramming solutions of maximal difference and uses them as targets for a neighborhood search to locate high-quality integer solutions. While multiple diverse solutions provide a good coverage of the solution landscape, the neighborhood search reduces the computational burden in searching for good integer solutions. Preliminary results on a set of benchmark problems have shown that the algorithm is computationally effective, providing multiple high-quality solutions at faster convergence rates than state-of-the-art commercial integer program solvers.
We discuss the problem of sequencing precedence-constrained jobs on a single machine to minimize the average weighted completion time. This problem has attracted much attention in the mathematical programming communit...
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We discuss the problem of sequencing precedence-constrained jobs on a single machine to minimize the average weighted completion time. This problem has attracted much attention in the mathematical programming community since Sidney's pioneering work in 1975 (Sidney, J. B. 1975. Decomposition algorithms for single machine scheduling with precedence relations and deferral costs. Operations Research 23 283-298). We look at the problem from a polyhedral perspective and uncover a relation between Sidney's decomposition theorem and different linear programming relaxations. More specifically, we present a generalization of Sidney's result, which particularly allows us to reason that virtually all known 2-approximation algorithms are consistent with his decomposition. Moreover, we establish a connection between the single-machine scheduling problem and the vertex cover problem. Indeed, in the special case of series-parallel precedence constraints, we prove that the sequencing problem can be seen 'as a special case of the vertex cover problem. We also. argue that this result is true for general precedence constraints if one can show that a certain integer program represents a valid formulation of the sequencing problem. Finally, we give a 3/2-approximation algorithm for two-dimensional partial orders, and we also provide a characterization of the active inequalities of a linear programming relaxation in completion time variables.
In the 0-extension problem, we are given a weighted graph with some nodes marked as terminals and a semimetric on the set of terminals. Our goal is to assign the rest of the nodes to terminals so as to minimize the su...
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In the 0-extension problem, we are given a weighted graph with some nodes marked as terminals and a semimetric on the set of terminals. Our goal is to assign the rest of the nodes to terminals so as to minimize the sum, over all edges, of the product of the edge's weight and the distance between the terminals to which its endpoints are assigned. This problem generalizes the multiway cut problem of Dahlhaus et al. [SIAM J. Comput., 23 (1994), pp. 864-894] and is closely related to the metric labeling problem introduced by Kleinberg and Tardos [Proceedings of the 40th IEEE Annual Symposium on Foundations of Computer Science, New York, 1999, pp. 14-23]. We present approximation algorithms for 0-Extension. In arbitrary graphs, we present a O(log k)-approximation algorithm, k being the number of terminals. We also give O(1)-approximation guarantees for weighted planar graphs. Our results are based on a natural metric relaxation of the problem previously considered by Karzanov [European J. Combin., 19 ( 1998), pp. 71-101]. It is similar in flavor to the linear programming relaxation of Garg, Vazirani, and Yannakakis [ SIAM J. Comput., 25 (1996), pp. 235-251] for the multicut problem, and similar to relaxations for other graph partitioning problems. We prove that the integrality ratio of the metric relaxation is at least c root lg k for a positive c for infinitely many k. Our results improve some of the results of Kleinberg and Tardos, and they further our understanding on how to use metric relaxations.
In this paper, we present an integer programming formulation of the prize collecting Steiner problem in graphs (PCSPG) and describe an algorithm to obtain lower bounds for the problem. The algorithm is based on polyhe...
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In this paper, we present an integer programming formulation of the prize collecting Steiner problem in graphs (PCSPG) and describe an algorithm to obtain lower bounds for the problem. The algorithm is based on polyhedral cutting planes and is initiated with tests that attempt to reduce the size of the input graph. Computational experiments were carried out to evaluate the strength of the formulation through its linear programming relaxation. On 96 out of the 114 instances tested, integer solutions were found (thus generating optimal PCSPG solutions). (C) 2003 Elsevier B.V. All rights reserved.
In this paper, we present an integer programming formulation of the prize collecting Steiner problem in graphs (PCSPG) and describe an algorithm to obtain lower bounds for the problem. The algorithm is based on polyhe...
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In this paper, we present an integer programming formulation of the prize collecting Steiner problem in graphs (PCSPG) and describe an algorithm to obtain lower bounds for the problem. The algorithm is based on polyhedral cutting planes and is initiated with tests that attempt to reduce the size of the input graph. Computational experiments were carried out to evaluate the strength of the formulation through its linear programming relaxation. On 96 out of the 114 instances tested, integer solutions were found (thus generating optimal PCSPG solutions). (C) 2003 Elsevier B.V. All rights reserved.
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