This paper describes the formulation of a nonlinear mixed integer programming model for a large-scale product development and distribution problem and the design and computational implementation of a special purpose a...
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We consider a setting where a team of multiple robots has to fulfill a mission in a specifically defined formation in a partially known environment. In many real environments, not all obstacles are previously known, b...
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ISBN:
(纸本)9788995003848
We consider a setting where a team of multiple robots has to fulfill a mission in a specifically defined formation in a partially known environment. In many real environments, not all obstacles are previously known, but often most of them. For the planning of the optimal trajectory along these obstacles a mixed integer programming algorithm is used. If during the mission at least one of the robots detects a previously unknown obstacle, the control on each robot switches from centralized formation control to decentralized control. In this case, each robot is able to use its own set of Fuzzy Systems for obstacle avoidance and returns to the optimal trajectory after passing the unknown obstacles. This concept allows the robots to find the optimal trajectories for the mission task in known areas using the mixed integer programming. In unknown or for the mixed integer programming too complex scenarios the robots have to use the information based on their limited onboard sensors. With the sensor information they are in most cases able to find at least a possible way through the obstacles by using a set of onboard Fuzzy Systems for robot control.
During the last decade, significant progress has been made in solving the Protein Threading Problem (PTP). However, all previous approaches to PTP only perform global sequence-structure alignment. This obvious limitat...
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During the last decade, significant progress has been made in solving the Protein Threading Problem (PTP). However, all previous approaches to PTP only perform global sequence-structure alignment. This obvious limitation is in clear contrast with the "world of sequences", where local sequence-sequence alignments are widely used to find functionally important regions in families of proteins. This paper presents a novel approach to PIP which allows to align a part of a protein structure onto a protein sequence in order to detect local similarities. We show experimentally that such local sequence-structure alignments improve the quality of the prediction. Our approach is based on mixed integer programming (MIP) which has been shown to be very successful in this domain. We describe five MIP models for local sequence-structure alignments, compare and analyze their performances by using ILOG CPLEX 10 solver on a benchmark of proteins. (C) 2010 Elsevier B.V. All rights reserved.
This paper presents a description of a mixed integer programming (MIP) solution for solving the PJM Unit Commitment problem. Included is a description of the Day-ahead market clearing problem and the Reliability Analy...
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ISBN:
(纸本)078039156X
This paper presents a description of a mixed integer programming (MIP) solution for solving the PJM Unit Commitment problem. Included is a description of the Day-ahead market clearing problem and the Reliability Analysis problem. This is followed by an overview of the MIP development process and some selected comparisons with our previously existing Lagrangian Relaxation (LR) algorithm. The paper describes many of the inherent problems associated with MIP solutions and illustrates how these issues were dealt with to provide a fast, accurate, and robust MIP solution.
The inclusion of generator hot, warm and cold start up costs is critical to accurately model the unit commitment problem faced by electric utilities throughout the world. Furthermore, there is growing popularity in us...
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ISBN:
(纸本)9789810594237
The inclusion of generator hot, warm and cold start up costs is critical to accurately model the unit commitment problem faced by electric utilities throughout the world. Furthermore, there is growing popularity in using mixed integer programming (MIP) solvers to tackle the entire unit commitment problem provided a MIP formulation exists. This paper presents an explicit MIP formulation of the hot, warm and cold costs and constraints involved in starting a generator. This formulation is tested on a three generator test system to prove its correctness.
In this paper we describe the automatic instantiation of a Variable Neighborhood Descent procedure from a mixed integer programming model. We extend a recent approach in which a single neighborhood structure is automa...
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In this paper we describe the automatic instantiation of a Variable Neighborhood Descent procedure from a mixed integer programming model. We extend a recent approach in which a single neighborhood structure is automatically designed from a mixed integer programming model using a combination of automatic extraction of semantic features and automatic algorithm configuration. Computational results on four well-known combinatorial optimization problems show improvements over both a previous model-derived Variable Neighborhood Descent procedure and the approach with a single automatically-designed neighborhood structure. (C) 2017 The Authors. Published by Elsevier Ltd.
Many of the most successful classifiers are based on convex surrogate loss functions. However, it is widely accepted that the 0 - 1 loss would be more natural for classification performance evaluation and many surroga...
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ISBN:
(纸本)9781479941957
Many of the most successful classifiers are based on convex surrogate loss functions. However, it is widely accepted that the 0 - 1 loss would be more natural for classification performance evaluation and many surrogate loss functions can be understood as convex approximations to the 0 - 1 loss. Therefore, in this paper, we attempt to minimize the 0 - 1 loss directly via mixed integer programming and a maximum margin 0 - 1 loss is presented. To test the performance of the proposed loss measurement, two maximum margin 0 - 1 loss classifiers are implemented for binary classification and semi-supervised classification respectively. According to the experiment results of the publicly available UCI datasets, the maximum margin 0 - 1 loss approach has achieved superior performance. Meanwhile, in term of computational efficiency, with the rapid development of mixed integer programming in recent years, the state-of-art solvers can output the global optimum solution of the proposed approach in seconds when the number of training instances N and the dimension of feature space D are relatively small ( Empirically N <= 100;D <= 20). Therefore, it can already be adopted to solve small-scale classification problems in the real world.
The objective of this study is to propose a mixed integer programming model which can help make-to-order (MTO) companies to make proper decisions in accepting or rejecting customers' orders. The proposed model can...
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ISBN:
(纸本)9780982148945
The objective of this study is to propose a mixed integer programming model which can help make-to-order (MTO) companies to make proper decisions in accepting or rejecting customers' orders. The proposed model can solve small capacity planning problems with the objective function of maximizing the profit, with the condition that the orders must be delivered on time. If the company accepts the orders, three decisions can be made within the planning horizon, which are to do the job by normal time, overtime, or to outsource it. A case study was conducted in a MTO company and the proposed model was solved by using ILOG Optimization programming Language (OPL). The reasonableness of the optimum solution shows that the model is applicable in practice.
Optimizing the operation of thermal power plant auxiliaries can effectively reduce the power consumption rate and improve production efficiency. This paper establishes the optimal operation model for variable-speed pu...
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ISBN:
(纸本)9783037852668
Optimizing the operation of thermal power plant auxiliaries can effectively reduce the power consumption rate and improve production efficiency. This paper establishes the optimal operation model for variable-speed pumps and fans, which are the main auxiliaries in thermal power plant. The model is based on the operating characteristics of pumps and fans and considers parallel and series operation. The object is to minimize the power of auxiliaries;the constraints contain the requirements of system flow or head, speed limits, flow limits, power limits and pipeline performance. Because of the complexity of the model, the pumps and fans operating performance curves are transferred to piece-wise linear curves at first, then a new 0-1 variable is introduces to characterize the choice of a different Q-P curve at a different speed. The model has been converted to mixedinteger linear programming problem and uses commercial modeling tools to solve. The case is to verify the effectiveness of this method.
We introduce a new plan repair method for problems cast as mixedinteger Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the use of Supervised Learning method for...
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ISBN:
(纸本)9780769542638
We introduce a new plan repair method for problems cast as mixedinteger Programs. In order to tackle the inherent complexity of these NP-hard problems, our approach relies on the use of Supervised Learning method for the offline construction of a predictor which takes the problem's parameters as input and infers values for the discrete optimization variables. This way, the online resolution time of the plan repair problem can be greatly decreased by avoiding a large part of the combinatorial search among discrete variables. This contribution was motivated by the large-scale problem of intra-daily recourse strategy computation in electrical power systems. We report and discuss results on this benchmark, illustrating the different aspects and mechanisms of this new approach which provided close-to-optimal solutions in only a fraction of the computational time necessary for existing solvers.
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