Global optimization methods based on Lipschitz bounds have been analyzed and applied widely to solve various optimization problems. In this paper a bound for Lipschitz function is proposed, which is computed using fun...
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Global optimization methods based on Lipschitz bounds have been analyzed and applied widely to solve various optimization problems. In this paper a bound for Lipschitz function is proposed, which is computed using function values at the vertices of a simplex and the radius of the circumscribed sphere. The efficiency of a branch and bound algorithm with proposed bound and combinations of bounds is evaluated experimentally while solving a number of multidimensional test problems for global optimization. The influence of different bounds on the performance of a branch and bound algorithm has been investigated.
The topic of this paper is the cyclic job shop problem which aims at minimizing the cycle time under precedence and resource constraints. Based on graph theory, we propose a new branch and bound enumeration procedure ...
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The topic of this paper is the cyclic job shop problem which aims at minimizing the cycle time under precedence and resource constraints. Based on graph theory, we propose a new branch and bound enumeration procedure to solve this problem. We compare the new procedure with other exact methods and present numerical test results.
We propose a new adaptive branch and bound algorithm for selecting the optimal subset of features in pattern recognition applications. The algorithm improves the search speed by avoiding unnecessary criterion function...
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We propose a new adaptive branch and bound algorithm for selecting the optimal subset of features in pattern recognition applications. The algorithm improves the search speed by avoiding unnecessary criterion function calculations at nodes in the solution tree. Our algorithm includes the following new properties: (i) ordering the tree nodes by the significance of features during construction of the tree, Oil obtaining a large "good" initial bound by a floating search method, (iii) a new method to select an initial starting search level in the tree. and (iv) a new adaptive jump search strategy to select subsequent search levels to avoid redundant criterion function calculations. Our experimental results for four different databases demonstrate that our method is significantly faster than other versions of the branch and bound algorithm when the database has more than 30 features. (c) 2007 Elsevier B.V.. All rights reserved.
The paper studies a train scheduling problem faced by railway infrastructure managers during real-time traffic control. When train operations are perturbed, a new conflict-free timetable of feasible arrival and depart...
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The paper studies a train scheduling problem faced by railway infrastructure managers during real-time traffic control. When train operations are perturbed, a new conflict-free timetable of feasible arrival and departure times needs to be recomputed, such that the deviation from the original one is minimized. The problem can be viewed as a huge job shop scheduling problem with no-store constraints. We make use of a careful estimation of time separation among trains, and model the scheduling problem with an alternative graph formulation. We develop a branch and bound algorithm which includes implication rules enabling to speed up the computation. An experimental study, based on a bottleneck area of the Dutch rail network, shows that a truncated version of the algorithm provides proven optimal or near optimal solutions within short time limits. (c) 2006 Elsevier B.V. All rights reserved.
Within the framework of any bilevel decision problem, a leader's decision at the upper level is influenced by the reaction of their follower at the lower level. When multiple followers are involved in a bilevel de...
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Within the framework of any bilevel decision problem, a leader's decision at the upper level is influenced by the reaction of their follower at the lower level. When multiple followers are involved in a bilevel decision problem, the leader's decision will not only be affected by the reactions of those followers, but also by the relationships among those followers. One of the popular situations within this framework is where these followers are uncooperatively making decisions while having cross reference of decision information, called a referential-uncooperative situation in this paper. The well-known branch and bound algorithm has been successfully applied to a one-leader-and-one-follower linear bilevel decision problem. This paper extends this algorithm to deal with the above mentioned linear bilevel multi-follower decision problem by means of a linear referential uncooperative bilevel multi-follower decision model. It then proposes an extended branch and bound algorithm to solve this problem with a set of illustrative examples in a referential-uncooperative situation.
We consider the one-machine scheduling problem with minimum and maximum time lags while minimizing the makespan. This problem typically arises in a manufacturing environment where the next job has to be carried out wi...
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We consider the one-machine scheduling problem with minimum and maximum time lags while minimizing the makespan. This problem typically arises in a manufacturing environment where the next job has to be carried out within a specific time range after the completion of the immediately preceding job. We describe a branch and bound algorithm, based on the input and output of a clique and the relevant propositions, for finding the optimal waiting times. The computational experiments give promising results, showing whether a given instance is feasible or infeasible. With the proposed branch and bound algorithm we can either find an optimal schedule or establish the infeasibility within an acceptable run time. (c) 2006 Elsevier B.V. All rights reserved.
This paper describes a novel optimization-based approach to conflict resolution in air traffic control, based on geometric programming. A key feature of this approach is its ability to also take into account various m...
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This paper describes a novel optimization-based approach to conflict resolution in air traffic control, based on geometric programming. A key feature of this approach is its ability to also take into account various metering directives issued by the traffic flow management level, in contrast to most methods that focus purely on aircraft separation issues. Moreover, the proposed methodology can account for some of the nonlinearities present in the formulations of conflict resolution Problems, while incurring only a small penalty in computation time with respect to the fastest linear-programming-based approaches. Integer variables can be introduced to improve the quality of the solutions and to include combinatorial choices, for example, to optimize over aircraft sequences in merging streams. Simulation results demonstrate the efficiency of the approach on various aircraft separation problems, including miles-in-trail and minutes-in-trail restrictions through airspace fixes and boundaries.
In the paper, we study a flexible assembly line design problem with equipment decisions. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no small...
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In the paper, we study a flexible assembly line design problem with equipment decisions. We assume the task times and equipment costs are correlated in the sense that for all tasks the cheaper equipment gives no smaller task time. Given the cycle time and number of workstations we aim to find the assignment of tasks and equipment to the workstations so as to minimise the total equipment cost. We develop a branch and bound algorithm that uses powerful lower bounds and reduction mechanisms. Our computational experiments have revealed that our algorithm can solve large-sized problem instances in reasonable solution times.
The design and implementation of assembly-line systems have been critical issues for companies since the first assembly-line was started at the Ford Highland Plant in 1913. From that time onwards, most companies have ...
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The design and implementation of assembly-line systems have been critical issues for companies since the first assembly-line was started at the Ford Highland Plant in 1913. From that time onwards, most companies have met with various problems at the design and implementation stages of assembly-line systems, two of which are the allocation of different work elements to various workstations and the proper equipment selection for workstations. Therefore, in this article, to overcome both the above-mentioned problems, we propose an integrated approach in which a branch and bound algorithm and the analytic hierarchy process (AHP) method are used together. First, the branch and bound algorithm is used to generate a list of assembly-line design alternatives. Then, the generated alternatives are evaluated using the AHP method to determine an optimum solution (the best alternative) at minimum equipment cost. The AHP method is one of the most commonly used multiple-criteria decision-making methods in the literature, and evaluates both qualitative and quantitative evaluation criteria represented in a hierarchical form. The proposed approach is also illustrated on a sample case study.
Associating textual annotations/tags with multimedia content is among the most effective approaches to organize and to support search over digital images and multimedia databases. Despite advances in multimedia analys...
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Associating textual annotations/tags with multimedia content is among the most effective approaches to organize and to support search over digital images and multimedia databases. Despite advances in multimedia analysis, effective tagging remains largely a manual process wherein users add descriptive tags by hand, usually when uploading or browsing the collection, much after the pictures have been taken. This approach, however, is not convenient in all situations or for many applications, e.g., when users would like to publish and share pictures with others in real time. An alternate approach is to instead utilize a speech interface using which users may specify image tags that can be transcribed into textual annotations by employing automated speech recognizers. Such a speech-based approach has all the benefits of human tagging without the cumbersomeness and impracticality typically associated with human tagging in real time. The key challenge in such an approach is the potential low recognition quality of the state-of-the-art recognizers, especially, in noisy environments. In this paper, we explore how semantic knowledge in the form of co-occurrence between image tags can be exploited to boost the quality of speech recognition. We postulate the problem of speech annotation as that of disambiguating among multiple alternatives offered by the recognizer. An empirical evaluation has been conducted over both real speech recognizer's output as well as synthetic data sets. The results demonstrate significant advantages of the proposed approach compared to the recognizer's output under varying conditions.
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