We propose a novel approach for navigating in polygonal environments by synthesizing controllers that take as input relative displacement measurements with respect to a set of landmarks. Our algorithm is based on solv...
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ISBN:
(纸本)9781665441971
We propose a novel approach for navigating in polygonal environments by synthesizing controllers that take as input relative displacement measurements with respect to a set of landmarks. Our algorithm is based on solving a sequence of robust min-max linear programming problems on the elements of a cell decomposition of the environment. The optimization problems are formulated using linear Control Lyapunov Function (CLF) and Control Barrier Function (CBF) constraints, to provide stability and safety guarantees, respectively. The inner maximization problem ensures that these constraints are met by all the points in each cell, while the outer minimization problem balances the different constraints in a robust way. We show that the min-max optimization problems can be solved efficiently by transforming it into regular linear programming via the dualization of the inner maximization problem. We test our algorithm to agents with first and second order integrator dynamics, although our approach is in principle applicable to any system with piecewise linear dynamics. Through our theoretical results and simulations, we show that the resulting controllers: are optimal (with respect to the criterion used in the formulation), are applicable to linear systems of any order, are robust to changes to the start location (since they do not rely on a single nominal path), and to significant deformations of the environment.
Purpose The purpose of this study is to present a new failure mode and effects analysis (FMEA) approach based on fuzzy multi-criteria decision-making (MCDM) methods and multi-objective programming model for risk asses...
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Purpose The purpose of this study is to present a new failure mode and effects analysis (FMEA) approach based on fuzzy multi-criteria decision-making (MCDM) methods and multi-objective programming model for risk assessment in the planning phase of the oil and gas construction projects (OGCP) in Iran. Design/methodology/approach This research contains multiple steps. First, 19 major potential health and safety executive (HSE) risks in OGCP were classified into six categories with the Delphi method. These factors were distinguished by the review of project documentation, checklist analysis and consulting with experts. Then, using the fuzzy SWARA method, the authors calculated the weights of major HSE risks. Subsequently, FMEA and PROMETHEE approaches were used to identify the priority of main risk factors. Eventually, a binary multi-objective linear programming approach was developed to select the risk response strategies, and an augmented e-constraint method (AECM) was used. Findings Regarding the project triple well-known constraints of time, cost and quality, which organizations usually confront, the HSE risks of OGCP were identified and prioritized. Also, the appropriate risk response strategies were also suggested to the managers to be adopted regarding the situations. Originality/value The present research points at the HSE risks' assessment integrating the fuzzy FMEA, step-wise weight assessment ratio analysis and PROMETHEE techniques with the AECM. Further to the authors' knowledge, the quantitative assessment of the HSE risks of OGCP has not been done using the combination of the fuzzy FMEA, MCDM and AECMs.
The paper addresses the issue of layout bugs, in which elements of a web page may overlap, become misaligned or protrude from their parent container for fortuitous reasons. It proposes a technique to apply corrections...
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ISBN:
(纸本)9783030742966;9783030742959
The paper addresses the issue of layout bugs, in which elements of a web page may overlap, become misaligned or protrude from their parent container for fortuitous reasons. It proposes a technique to apply corrections to a rendered page by formulating its current state and associated layout constraints into a Mixed Integer linear programming problem. An off-the-shelf numerical solver is used to generate a layout that satisfies the constraints, in such a way that disruptions to the original page are minimized. A probe then injects these corrections in the form of a temporary "hotfix". The approach has been implemented and tested on samples of real-world web pages;using techniques that aim to reduce the size of the optimization problem, a solution can often be computed in a few seconds on commodity hardware.
System-Optimal Dynamic Traffic Assignment (SO-DTA) problem optimizes the time-dependent traffic flow of a transportation network, with varied objectives and complicated constraints. Traffic management applications of ...
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ISBN:
(纸本)9781728189642
System-Optimal Dynamic Traffic Assignment (SO-DTA) problem optimizes the time-dependent traffic flow of a transportation network, with varied objectives and complicated constraints. Traffic management applications of Intelligent Transports Systems (ITS), such as emergency evacuation, network optimization, and route planning, rely on SO-DTA models to obtain sophisticated solutions to optimize network performance. In this paper, an improved route-based linear programming (IRLP) optimization model is proposed, specially tailored for the emergency evacuation problem of pedestrians in ITS. The proposed model utilizes the Cell Transmission Model (CTM) and linear programming to model the pedestrian evacuation and introduces penalty labels in the IRLP formulations to solve the holding-back flow issue. Besides, when designing the model, the categories of transmission cells are simplified to make the model more practical, compared to some previous research work. Finally, a series of simulation experiments, including the comparison to the real-world shortest-path evacuation strategies, are conducted to showcase the effectiveness in saving valuable evacuation time.
We present PDLP, a practical first-order method for linear programming (LP) that can solve to the high levels of accuracy that are expected in traditional LP applications. In addition, it can scale to very large probl...
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ISBN:
(纸本)9781713845393
We present PDLP, a practical first-order method for linear programming (LP) that can solve to the high levels of accuracy that are expected in traditional LP applications. In addition, it can scale to very large problems because its core operation is matrix-vector multiplications. PDLP is derived by applying the primal-dual hybrid gradient (PDHG) method, popularized by Chambolle and Pock (2011), to a saddle-point formulation of LP. PDLP enhances PDHG for LP by combining several new techniques with older tricks from the literature;the enhancements include diagonal preconditioning, presolving, adaptive step sizes, and adaptive restarting. PDLP improves the state of the art for first-order methods applied to LP. We compare PDLP with SCS, an ADMM-based solver, on a set of 383 LP instances derived from MIPLIB 2017. With a target of 10 relative accuracy and 1 hour time limit, PDLP achieves a 6.3x reduction in the geometric mean of solve times and a 4.6x reduction in the number of instances unsolved (from 227 to 49). Furthermore, we highlight standard benchmark instances and a large-scale application (PageRank) where our open-source prototype of PDLP, written in Julia, outperforms a commercial LP solver.
In this study, we consider a particular version of the hybrid flexible flow shop (HFFS) scheduling problem, inspired from a real -life application in a printing industry. The considered problem is a variation of the c...
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In this study, we consider a particular version of the hybrid flexible flow shop (HFFS) scheduling problem, inspired from a real -life application in a printing industry. The considered problem is a variation of the classical Flow shop problem, in which specific constraints are jointly considered, such as nonidentical parallel machines, sequence -dependent setups on machines, machine eligibility, and precedence constraints among jobs, in order to minimize the total tardiness time. After a problem description, a mathematical model, in form of mixed integer linear programming (MILP) model, that incorporates these aspects is developed and evaluated using ILOG Cplex software. Copyright (C) 2021 The Authors.
A low-complexity distribution matching algorithm that aims to achieve high information rate for short blocklength probabilistic shaping by linear programming is proposed. At AIR of 4 bits/symbol and SNR of 11.87 dB, t...
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ISBN:
(纸本)9781665438681
A low-complexity distribution matching algorithm that aims to achieve high information rate for short blocklength probabilistic shaping by linear programming is proposed. At AIR of 4 bits/symbol and SNR of 11.87 dB, the distribution matching blocklength is shortened by 256 times compared with CCDM.
Community detection is a fundamental challenge in network science and graph theory that aims to reveal nodes' structures. While most methods consider Modularity as a community quality measure, Max-Min Modularity i...
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ISBN:
(纸本)9788395918384
Community detection is a fundamental challenge in network science and graph theory that aims to reveal nodes' structures. While most methods consider Modularity as a community quality measure, Max-Min Modularity improves the accuracy of the measure by penalizing the Modularity quantity when unrelated nodes are in the same community. In this paper, we propose a community detection approach based on linear programming using Max-Min Modularity. The experimental results show that our algorithm has a better performance than the previously known algorithms on some well-known instances.
The existence of strongly polynomial-time algorithm for linear programming is a cross century international mathematical problem, whose breakthrough will solve a major theoretical crisis for the development of artific...
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ISBN:
(纸本)9781450391153
The existence of strongly polynomial-time algorithm for linear programming is a cross century international mathematical problem, whose breakthrough will solve a major theoretical crisis for the development of artificial intelligence. In order to make it happen, this paper proposes three solving techniques based on the conecutting theory: 1. The selection of cutter: principles highest vs. deepest;2. The algorithm of column elimination, which is more convenient and effective than the Ye-column elimination theorem;3. A step-down algorithm for a feasible point horizontally shifts to the center and then falls down to the bottom of the dual feasible region D. There will be a nice work combining three techniques, the tri-skill is variant Simplex algorithm to be expected to help readers building the strong polynomial algorithms. Besides, a variable weight optimization method is proposed in the paper, which opens a new window to bring the linear programming into uncomplicated calculation.
We propose an end-to-end pipeline to robustly generate high-quality, high-order and coarse quadrilateral meshes on CAD models. This kind of mesh enables the use of high-order analysis techniques such as high-order fin...
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ISBN:
(数字)9781624106101
ISBN:
(纸本)9781624106101
We propose an end-to-end pipeline to robustly generate high-quality, high-order and coarse quadrilateral meshes on CAD models. This kind of mesh enables the use of high-order analysis techniques such as high-order finite element methods or isogeometric analysis. An initial unstructured mesh is generated;this mesh contains a low number of irregular vertices but these are not necessarily aligned, causing a very dense quad layout. A T-mesh is built on the mesh which allows to modify its topology by assigning new integer lengths to the T-mesh arcs. The task of simplifying the quad layout can be formulated as an Integer linear Program which is solved efficiently using an adequate solver. Finally, a high-order quad mesh is extracted from the optimized topology. Validation on several CAD models shows that our approach is fast, robust, strictly respects the CAD features, and achieves interesting results in terms of coarseness and quality.
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