The paper concerns a small flexible manufacturing system consisting of three CNC machines: a lathe machine, milling machine and measurement center and a single robot, located at the Poznan University of Technology. A ...
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The paper concerns a small flexible manufacturing system consisting of three CNC machines: a lathe machine, milling machine and measurement center and a single robot, located at the Poznan University of Technology. A short description of the production environment, which can be modeled as the extended job shop system with open shop sections within particular jobs, is followed by the proposition of a branch and bound method. It optimizes production plans within a single shift in order to minimize the late work, i.e. the amount of work executed after a given due date. Based on results of computational experiments, conclusions are formulated on the efficiency of the B&B algorithm and on the behavior of FMS under consideration. (c) 2006 Elsevier Ltd. All rights reserved.
An exact algorithm is proposed to solve a scheduling problem of a robotic production system in which multi-type parts are processed and parts are not allowed to wait on the machines. Finding an optimal schedule in suc...
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ISBN:
(纸本)9781424413119
An exact algorithm is proposed to solve a scheduling problem of a robotic production system in which multi-type parts are processed and parts are not allowed to wait on the machines. Finding an optimal schedule in such a production system is equivalent to finding two types of correlative sequences: parts input sequence and robot moves sequence. We show that the entering times of parts are the decision variables of the problem. We formulate our problem using the notion of prohibited intervals and solve it by enumerating intervals for linear functions of the decision variables, which is accomplished with a branch and bound procedure. Computational results on randomly generated test instances indicate that the algorithm is effective.
Feature selection plays an important role in pattern classification. In this paper, we present an improved branch and bound algorithm for optimal feature subset selection. This algorithm searches for an optimal soluti...
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Feature selection plays an important role in pattern classification. In this paper, we present an improved branch and bound algorithm for optimal feature subset selection. This algorithm searches for an optimal solution in a large solution tree in an efficient manner by cutting unnecessary paths which are guaranteed not to contain the optimal solution. Our experimental results demonstrate the effectiveness of the new algorithm. (C) 2003 Elsevier Science B.V. All rights reserved.
In this paper, a two-stage assembly scheduling problem is considered with the objective of minimizing the total weighted flowtime. A lower bounding procedure and a dominance criterion are developed and incorporated in...
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In this paper, a two-stage assembly scheduling problem is considered with the objective of minimizing the total weighted flowtime. A lower bounding procedure and a dominance criterion are developed and incorporated into a branch and bound procedure. A heuristic procedure is also used to derive an initial upper bound. Computational results of the algorithm are presented.
In this paper, the classical mean-variance portfolio model is modified for calculating a globally optimal portfolio under concave transaction costs. A non-decreasing concave function is employed to approximate origin ...
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In this paper, the classical mean-variance portfolio model is modified for calculating a globally optimal portfolio under concave transaction costs. A non-decreasing concave function is employed to approximate origin transaction cost function. The resulting model is a. D-C (difference of two convex functions) programming and a branch and bound algorithm is designed to solve the problem. A series Of numerical experiments on the model is presented. The history data of nine stocks in Shan Xi province is used in experiments, and efficient frontiers generated from the resulting model with different limitations on investments are presented to show the effect of the model and the efficiency of the algorithm solving the model. (c) 2005 Elsevier Inc. All rights reserved.
An addition chain for a natural number n is a sequence 1 = a(0) < a(1) <. . . a(r) = n of numbers such that for each 0 < i <= r, a(i) = a(j) + a(k) for some 0 <= k <= j < i. An improvement by a fa...
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An addition chain for a natural number n is a sequence 1 = a(0) < a(1) <. . . a(r) = n of numbers such that for each 0 < i <= r, a(i) = a(j) + a(k) for some 0 <= k <= j < i. An improvement by a factor of 2 in the generation of all minimal (or one) addition chains is achieved by finding sufficient conditions for star steps, computing what we will call nonstar lower bound in a minimal addition chain and omitting the sorting step.
One of the most important objectives of the storage and pickup operations in block stacking systems is to minimize the number of relocations during the pickup operation. This study suggests two methods for determining...
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One of the most important objectives of the storage and pickup operations in block stacking systems is to minimize the number of relocations during the pickup operation. This study suggests two methods for determining the locations of relocated blocks. First, a branch-and-bound (B&B) algorithm is suggested. Next, a decision rule is proposed by using an estimator for an expected number of additional relocations for a stack. The performance of the decision rule was compared with that of the B&B algorithm. (c) 2004 Elsevier Ltd. All rights reserved.
In this paper several equivalent formulations for the quadratic binary programming problem are presented. Based on these formulations we describe four different kinds of strategies for estimating lower bounds of the o...
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In this paper several equivalent formulations for the quadratic binary programming problem are presented. Based on these formulations we describe four different kinds of strategies for estimating lower bounds of the objective function, which can be integrated into a branch and bound algorithm for solving the quadratic binary programming problem. We also give a theoretical explanation for forcing rules used to branch the variables efficiently, and explore several properties related to obtained subproblems. From the viewpoint of the number of subproblems solved, new strategies for estimating lower bounds are better than those used before. A variant of a depth-first branch and bound algorithm is described and its numerical performance is presented.
In manufacturing environments, machines are usually subject to down periods due to various reasons such as preventive maintenance activities, pre- accepted jobs and pre-known material shortages. Among these reasons, p...
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In manufacturing environments, machines are usually subject to down periods due to various reasons such as preventive maintenance activities, pre- accepted jobs and pre-known material shortages. Among these reasons, preventive maintenance, which is defined as the pre-planned maintenance activities to keep the machine in its operating state, has gained much more importance in recent years. In this thesis, we consider the single machine total flow time problem where the jobs are non-resumable and the machine is subject to preventive maintenance activities of known starting times and durations. We propose a number of optimality properties together with the upper and lower bounding procedures. Using these mechanisms, we build a branch and bound algorithm to find the optimal solution of the problem. Our extensive computational study on randomly generated test instances shows that our algorithm can solve large-sized problem instances with up to 80 jobs in reasonable times. We also study a two-alternative maintenance planning problem with minor and major maintenances. We give an optimizing algorithm to find the timing of the maintenances, when the job sequence is fixed.
This paper presents a branch and bound algorithm for computing opt inial replacement policies in a discrete-time, infinite-horizon, dynamic programming model of a binary coherent system with n statistically independen...
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This paper presents a branch and bound algorithm for computing opt inial replacement policies in a discrete-time, infinite-horizon, dynamic programming model of a binary coherent system with n statistically independent components, and then specializes the algorithm to consecutive k-out-of-n systems. The objective is to minimize the long-run expected average undiscounted cost per period. (Costs arise when the system fails and when failed components are replaced.) An earlier paper established the optimality of following a critical component policy (CCP), i.e., a policy specified by a critical component set and the rule: Replace a component if and only if it is failed and in the critical component set. Computing an optimal CCP is a optimization problem with it binary variables and a nonlinear objective function. Our branch and bound algorithm for solving this problem has memory storage requirement O(n) for consecutive k-out-of-n systems. Extensive computational experiments on such systems involving over 350,000 test problems with n ranging from 10 to 150 find this algorithm to be effective when n less than or equal to 40 or k is near n.
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