In this paper we study and solve two different variants of static knapsack problems with random weights: The stochastic knapsack problem with simple recourse as well as the stochastic knapsack problem with probabilist...
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In this paper we study and solve two different variants of static knapsack problems with random weights: The stochastic knapsack problem with simple recourse as well as the stochastic knapsack problem with probabilistic constraint. Special interest is given to the corresponding continuous problems and three different problem solving methods are presented. The resolution of the continuous problems allows to provide upper bounds in a branch-and-bound framework in order to solve the original problems. Numerical results on a dataset from the literature as well as a set of randomly generated instances are given.
This paper addresses the schemes to improve b&balgorithm performance for the NP-hard problem of scheduling N jobs on a single machine with due dates, sequence-dependent setup times,and no preemption,where the obj...
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This paper addresses the schemes to improve b&b algorithm performance for the NP-hard problem of scheduling N jobs on a single machine with due dates, sequence-dependent setup times,and no preemption,where the objective is to minimize the total *** dominance rules are proposed to reduce the expanded nodes and explored nodes.A comparison with Ragatz's b&b approaches indicates that the algorithm,which adopts our schemes,is competitive and has a certain advantage for larger problems.
We focus on deterministic global optimization (DGO) for nonconvex parameter estimation problems. Realistic and accurate solutions often require a fitting against very large measurement data sets, resulting in intracta...
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We focus on deterministic global optimization (DGO) for nonconvex parameter estimation problems. Realistic and accurate solutions often require a fitting against very large measurement data sets, resulting in intractable size for DGO. Thus, we aim at accelerating the branch-and-bound algorithmby using reduced data sets for constructing valid bounds. We focus on fitting the equation of state for propane, which is of high interest for the chemical industry. The resulting estimation problem is a challenging nonconvex mixed-integer nonlinear optimization problem. We investigate the validity of using reduced data sets by comparing how the lower and upper bounds change when replacing the full data set with different reduced data sets. We account for regions with high and low quality fits by considering the results for the whole feasible region and 100 different subregions. Our results indicate that both regions containing solution candidates and regions containing only low quality fits can be identified based on reduced data sets. Moreover, we observe that the average CPU time per branch-and-bound iteration typically decreases if reduced data sets are used.
In the work a single-machine scheduling problem is being considered, in which all tasks have a fixed availability (release) and delivery time. In the analyzed variant no-idle time is allowed on a machine. The purpose ...
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In the work a single-machine scheduling problem is being considered, in which all tasks have a fixed availability (release) and delivery time. In the analyzed variant no-idle time is allowed on a machine. The purpose of optimization is to determine such order of tasks that minimizes the makespan, i.e. the time of execution of all the tasks. There is also a number of properties of the problem presented, in particular there are formulated block eliminating properties for no-idle constraint. There was an exact b&b algorithmbased on the block properties proposed.
This paper describes a parallel algorithm solving the m-machines, n-jobs, permutation flow shop scheduling problem as well as its deployment on a Grid of computers (Grid'5000). Our algorithm is basically a paralle...
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ISBN:
(数字)9783642176258
ISBN:
(纸本)9783642176241
This paper describes a parallel algorithm solving the m-machines, n-jobs, permutation flow shop scheduling problem as well as its deployment on a Grid of computers (Grid'5000). Our algorithm is basically a parallelization of the well known branch and bound method, which is an exact method for solving combinatorial optimization problems. We present, in particular, a new strategy of parallelization which uses some directives of communication between all processors in order to update the value of the Upper bound. The purpose is to obtain the optimal scheduling of all the jobs as quickly as possible by modifying and adapting the classical sequential branch and bound method. The deployment of our application on the Grid gives good results and permits the resolution of new instances not yet resolved.
学位级别:M.C.R.P., Master of City and Regional Planning
This is a report of a professional project intended to act as an informational tool for the evaluation of a dynamic dispatch system at Embarcadero Station for the San Francisco Municipal Transportation Agency (SFMTA)....
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This is a report of a professional project intended to act as an informational tool for the evaluation of a dynamic dispatch system at Embarcadero Station for the San Francisco Municipal Transportation Agency (SFMTA). Systems that operate dispatch algorithms do so in response to ontime performance and reliability. The optimization problem is documented in many transportation contexts including airline networks, bus dispatch, and freight routing. According to the research, optimizing available options and re-routing based on available options can create a more efficient system that would minimize operating costs and improving service reliability for customers. The methodology presented here uses current headway information to dynamically change dispatch assignment between J, L, and M lines. The reassignment program was applied to randomly selected weekdays in March of 2012. After analysis it was determined that the application has the potential to decrease mean operating headways by up to 3% (or approximately 15 seconds).
An alternative formulation of the scheduling problem in a robot‐centered manufacturing cell has been described here, which was originally formulated by Lin et al. [7] as a mixed integer programming problem. An effici...
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An alternative formulation of the scheduling problem in a robot‐centered manufacturing cell has been described here, which was originally formulated by Lin et al. [7] as a mixed integer programming problem. An efficient procedure based on the branch and bound technique has been proposed. In order to reduce the complexity of the branching procedure, several sequencing rules [4] have been imbedded into the proposed procedure and an integrated algorithm has then been presented. The computational results have indicated the proposed algorithm to be efficient. Finally, conclusions and some suggestions are given.
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