Optimal Cycles for Persistent Homology Via Linear Programming

Author(s):  
Emerson G. Escolar ◽  
Yasuaki Hiraoka
2021 ◽  
Vol 4 ◽  
Author(s):  
Lu Li ◽  
Connor Thompson ◽  
Gregory Henselman-Petrusek ◽  
Chad Giusti ◽  
Lori Ziegelmeier

Cycle representatives of persistent homology classes can be used to provide descriptions of topological features in data. However, the non-uniqueness of these representatives creates ambiguity and can lead to many different interpretations of the same set of classes. One approach to solving this problem is to optimize the choice of representative against some measure that is meaningful in the context of the data. In this work, we provide a study of the effectiveness and computational cost of several ℓ1 minimization optimization procedures for constructing homological cycle bases for persistent homology with rational coefficients in dimension one, including uniform-weighted and length-weighted edge-loss algorithms as well as uniform-weighted and area-weighted triangle-loss algorithms. We conduct these optimizations via standard linear programming methods, applying general-purpose solvers to optimize over column bases of simplicial boundary matrices. Our key findings are: 1) optimization is effective in reducing the size of cycle representatives, though the extent of the reduction varies according to the dimension and distribution of the underlying data, 2) the computational cost of optimizing a basis of cycle representatives exceeds the cost of computing such a basis, in most data sets we consider, 3) the choice of linear solvers matters a lot to the computation time of optimizing cycles, 4) the computation time of solving an integer program is not significantly longer than the computation time of solving a linear program for most of the cycle representatives, using the Gurobi linear solver, 5) strikingly, whether requiring integer solutions or not, we almost always obtain a solution with the same cost and almost all solutions found have entries in {‐1,0,1} and therefore, are also solutions to a restricted ℓ0 optimization problem, and 6) we obtain qualitatively different results for generators in Erdős-Rényi random clique complexes than in real-world and synthetic point cloud data.


1997 ◽  
Vol 48 (7) ◽  
pp. 757-758
Author(s):  
B Kolman ◽  
R E Beck ◽  
M J Panik
Keyword(s):  

1985 ◽  
Vol 132 (3) ◽  
pp. 123 ◽  
Author(s):  
B.C. Clewer ◽  
M.R. Irving ◽  
M.J.H. Sterling

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1447-1452
Author(s):  
Vincent Mazauric ◽  
Ariane Millot ◽  
Claude Le Pape-Gardeux ◽  
Nadia Maïzi

To overcome the negative environemental impact of the actual power system, an optimal description of quasi-static electromagnetics relying on a reversible interpretation of the Faraday’s law is given. Due to the overabundance of carbon-free energy sources, this description makes it possible to consider an evolution towards an energy system favoring low-carbon technologies. The management for changing is then explored through a simplified linear-programming problem and an analogy with phase transitions in physics is drawn.


2020 ◽  
Vol 64 (1-4) ◽  
pp. 165-172
Author(s):  
Dongge Deng ◽  
Mingzhi Zhu ◽  
Qiang Shu ◽  
Baoxu Wang ◽  
Fei Yang

It is necessary to develop a high homogeneous, low power consumption, high frequency and small-size shim coil for high precision and low-cost atomic spin gyroscope (ASG). To provide the shim coil, a multi-objective optimization design method is proposed. All structural parameters including the wire diameter are optimized. In addition to the homogeneity, the size of optimized coil, especially the axial position and winding number, is restricted to develop the small-size shim coil with low power consumption. The 0-1 linear programming is adopted in the optimal model to conveniently describe winding distributions. The branch and bound algorithm is used to solve this model. Theoretical optimization results show that the homogeneity of the optimized shim coil is several orders of magnitudes better than the same-size solenoid. A simulation experiment is also conducted. Experimental results show that optimization results are verified, and power consumption of the optimized coil is about half of the solenoid when providing the same uniform magnetic field. This indicates that the proposed optimal method is feasible to develop shim coil for ASG.


2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.


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