This paper deals with a two-machine flowshop problem in which the machine at the first stage requires preventive maintenance activities that have to be started within a given cumulative working time limit after the pr...
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This paper deals with a two-machine flowshop problem in which the machine at the first stage requires preventive maintenance activities that have to be started within a given cumulative working time limit after the previous maintenance. That is, a maintenance activity can be started at any time unless the cumulative working time after the end of the previous maintenance exceeds the given limit. For the problem with the objective of minimizing total tardiness, we develop dominance properties and lower bounds for this scheduling problem as well as a heuristic algorithm, and suggest a branch and bound algorithm in which these properties, lower bounds, and heuristic algorithm are used. Computational experiments are performed to evaluate the algorithm and the results are reported.
Multiple Traveling Salesman Problem (MTSP) is able to model and solve various real-life applications such as multiple scheduling, multiple vehicle routing and multiple path planning problems, etc. While Traveling Sale...
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Multiple Traveling Salesman Problem (MTSP) is able to model and solve various real-life applications such as multiple scheduling, multiple vehicle routing and multiple path planning problems, etc. While Traveling Salesman Problem (TSP) focuses on searching a path of minimum traveling distance to visit all cities exactly once by one salesman, the objective of the MTSP is to find m paths for m salesmen with a minimized total cost - the sum of traveling distances of all salesmen through all of the respective cities covered. They have to start from a designated depot which is the departing and returning location of all salesmen. Since the MTSP is a NP-hard problem, a new effective Genetic algorithm with Local operators (GAL) is proposed in this paper to solve the MTSP and generate high quality solution within a reasonable amount of time for real-life applications. Two new local operators, branch and bound (BaB) and Cross Elimination (CE), are designed to speed up the convergence of the search process and improve the solution quality. Results demonstrate that GAL finds a better set of paths with a 9.62% saving on average in cost comparing to two existing MTSP algorithms.
An observer, whose task is to monitor a large and complex system M^ subject to malfunctions, may be interested in dealing with a simplified, abstracted model (M^A of it, at the expense of some loss in fault-detection ...
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An observer, whose task is to monitor a large and complex system M^ subject to malfunctions, may be interested in dealing with a simplified, abstracted model (M^A of it, at the expense of some loss in fault-detection ability. Let M^ be a finite- state machine whose inputs are modeled by stationary random variables. The abstraction A is effected by lumping M^'s states, inputs, and outputs into classes, to obtain a smaller probabilistic machine M^A. These ideas have been introduced in a previous paper, and the question of finding an optimal abstraction A* which minimizes the number of faults undetectable by the observer was posed. An algorithm for constructing the output component of the optimal abstraction A* is given in this paper. If there are no faults in the next-state map of M^, this construction is sufficient to minimize the number of single faults in the output map that are undetectable by the observer because of the abstraction. Some experiments carried out using the algorithm provide general insight into the tradeoff between simplifying M^ and making some faults in it undetectable. As a specific example, optimal output abstractions are found for a finite-state machine specification of the link level of the X.25 communication protocol.
Consider the production planning and scheduling on a single machine with finite constant production rate over a planning horizon N. For single-item production problem, we have characterised the structure of the optima...
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Consider the production planning and scheduling on a single machine with finite constant production rate over a planning horizon N. For single-item production problem, we have characterised the structure of the optimal solution when N approaches to infinity. This result suggests a near optimal solution when the planning horizon N is large. For multi-item production problem, we restrict our analysis on the Rotation Cycle policies. Under the assumptions of the policy, we convert the problem into a generalised travelling salesman problem and hence a branch and bound algorithm is proposed to solve the problem. For a given error bound of the solution, the algorithm can be further simplified to determine a near-optimal rotation cycle. (C) 2001 Published by Elsevier Science B.V.
This study addresses the problem of minimizing total tardiness on a single machine with unequal release dates. Dominance properties established in previous literatures and herein are adopted to develop branch and boun...
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This study addresses the problem of minimizing total tardiness on a single machine with unequal release dates. Dominance properties established in previous literatures and herein are adopted to develop branch and bound and heuristic procedures. Computational experiments were conducted to evaluate the approaches. The results revealed that the branch and bound algorithm is efficient in solving hard problems and easy problems that involve up to 50 and 500 jobs, respectively. The computational effectiveness of the heuristic is also reported. (C) 2007 Elsevier B.V. All rights reserved.
A procedure for solving the capacitor placement problem is presented. The objective is to determine the minimum investment required to satisfy suitable reactive constraints. Due to the discrete nature of reactive comp...
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A procedure for solving the capacitor placement problem is presented. The objective is to determine the minimum investment required to satisfy suitable reactive constraints. Due to the discrete nature of reactive compensation devices, optimal capacitor placement leads to a nonlinear programming problem with mixed (discrete and continuous) variables, It is solved with an iterative algorithm based on successive linearizations of the original nonlinear model. The mixed integer linear programming problem to be solved at each iteration of the procedure is tackled by applying both a deterministic method (branch and bound) and genetic algorithm techniques, A hybrid procedure, aiming to exploit the best features of both algorithms is also considered. The proposed procedures are tested and compared with reference to a small CIGRE system and two actual networks derived from the Italian transmission and distribution system.
Positional DNA sequencing by hybridization (PSBH) is a recently proposed enhancement of DNA sequencing by hybridization (SBH, potentially a powerful alternative to the DNA sequencing by gel electrophoresis). It has be...
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Positional DNA sequencing by hybridization (PSBH) is a recently proposed enhancement of DNA sequencing by hybridization (SBH, potentially a powerful alternative to the DNA sequencing by gel electrophoresis). It has been discussed in many papers and applied to large scale sequencing by hybridization. However, the computational part of PSBH reconstruction is a difficult problem, especially for the occurrence of hybridization errors. So far the problem has not been solved well. Taking PSBH as a combinatorial optimization problem, a novel reconstruction approach to PSBH is presented in this paper. The proposed approach accepts both the negative and positive errors and can greatly reduce ambiguities in the reconstruction of PSBH. The computational experiment shows that our algorithm works satisfactorily and correctly on the test data, especially for the positive errors and k-tuple repetitions. (c) 2006 Elsevier B.V. All rights reserved.
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.
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.
Numerical dependencies (NDs) are database constraints that limit the number of distinct Y-values that can appear together with any X-value, where both X and Y are sets of attributes in a relation schema. While it is k...
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Numerical dependencies (NDs) are database constraints that limit the number of distinct Y-values that can appear together with any X-value, where both X and Y are sets of attributes in a relation schema. While it is known that NDs are not finitely axiomatizable, there is no study on how to efficiently derive NDs using a set of sound (yet necessarily incomplete) rules. In this paper, after proving that solving the entailment problem for NDs using the chase procedure has exponential space complexity, we show that, given a set of inference rules similar to those used for functional dependencies, the membership problem for NDs is NP-hard. We then provide a graph-based characterization of NDs, which is exploited to design an efficient branch & boundalgorithm for ND derivation. Our algorithm adopts several optimization strategies that provide considerable speed-up over a naive approach, as confirmed by the results of extensive tests we made for efficiency and effectiveness using six different datasets. (C) 2012 Elsevier Ltd. All rights reserved.
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