scholarly journals Global optimization approach for circular and chloroplast genome assembly

2017 ◽  
Author(s):  
Sebastien François ◽  
Rumen Andonov ◽  
Dominique Lavenier ◽  
Hristo Djidjev
Keyword(s):  
Global Optimization ◽  
Genome Assembly ◽  
Programming Model ◽  
Optimal Solution ◽  
Optimization Approach ◽  
Gap Filling ◽  
Insert Size ◽  
Genome Scaffolding ◽  
Additional Constraints

AbstractWe describe a global optimization approach for genome assembly where the steps of scaffolding, gap-filling, and scaffold extension are simultaneously solved in the framework of a common objective function. The approach is based on integer programming model for solving genome scaffolding as a problem of finding a long simple path in a specific graph that satisfies additional constraints encoding the insert-size information. The optimal solution of this problem allows one to obtain new kind of contigs that we call distance-based contig. We test the algorithm on a benchmark of chloroplasts and compare the quality of the results with recent scaffolders.

scholarly journals Mixed Optimal Scheduling Model of Flexible Service System Based on Inverted Triangle

2019 ◽  
Vol 2019 ◽  
pp. 1-20 ◽  
Author(s):  
Shipei Hu ◽  
Yujun Sun
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Working Hours ◽  
Binary Integer Programming ◽  
Scheduling Model ◽  
Programming Software ◽  
Working Day ◽  
Zhejiang Provincial

In the study presented in this paper, we built a nonlinear binary integer programming model of a flexible scheduling problem for the Department of Zhejiang Provincial Local Tax Services. One difference between our model and typical ones is that whereas in the latter the number of open windows within each working day is fixed, in our model it is not. We used a variety of integer programming software in an attempt to solve our scheduling model; however, unfortunately we could not find an optimal solution. Thus, we tested all the combinations of different numbers of employees to construct the optimal solution. When we tested our model in the tax office of Lishui City, China, the average waiting time of taxpayers was less than 15 min and the employees working hours were clearly reduced. Thus, a noteworthy improvement in the quality of the service is achieved by the model.

scholarly journals Complete assembly of circular and chloroplast genomes based on global optimization

2019 ◽  
Vol 17 (03) ◽  
pp. 1950014
Author(s):  
Rumen Andonov ◽  
Hristo Djidjev ◽  
Sebastien François ◽  
Dominique Lavenier
Keyword(s):  
Genome Assembly ◽  
Mixed Integer Linear Programming ◽  
Optimization Problem ◽  
Sufficient Conditions ◽  
Mixed Integer ◽  
Gap Filling ◽  
Insert Size ◽  
Size Information ◽  
Chloroplast Genomes ◽  
Two Stages

This paper focuses on the last two stages of genome assembly, namely, scaffolding and gap-filling, and shows that they can be solved as part of a single optimization problem. Our approach is based on modeling genome assembly as a problem of finding a simple path in a specific graph that satisfies as many distance constraints as possible encoding the insert-size information. We formulate it as a mixed-integer linear programming (MILP) problem and apply an optimization solver to find the exact solutions on a benchmark of chloroplasts. We show that the presence of repetitions in the set of unitigs is the main reason for the existence of multiple equivalent solutions that are associated to alternative subpaths. We also describe two sufficient conditions and we design efficient algorithms for identifying these subpaths. Comparisons of the results achieved by our tool with the ones obtained with recent assemblers are presented.

A Cooperative Scheduling Model for Subway Trains

2012 ◽  
Author(s):  
Xiang Li ◽  
Xin Yang ◽  
Hongwei Wang ◽  
Shuai Su ◽  
Wenzhe Sun
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Electric Energy ◽  
Optimal Solution ◽  
Optimization Approach ◽  
Trip Time ◽  
Proposed Model ◽  
Time Window Constraints ◽  
Braking Phase ◽  
Cooperative Scheduling

For subway systems, the energy put into accelerating the trains can be reconverted into electric energy by using the motors as generators during braking phase. Generally speaking, except a small part is used for on-board purposes, most of the recovery energy is transmitted backwards along the conversion chain and fed back into the catenary. However, since the low catenary voltage DC systems, the transmission losses are very high. In order to improve the utilization of recovery energy, this paper proposes an optimization approach to cooperate the acceleration and brake times of successive trains such that the recovery energy from the braking train can be directly used by the accelerating train. First, we formulate a quadratic programming model to optimize the cooperative degree with trip time constraint and time window constraints. Furthermore, we solve the optimal solution by using the Kuhn-Tucker conditions. Finally, we present a numerical example based on the operation data from Beijing Yizhuang subway line of China, which illustrates that the proposed model can improve the cooperative degree by 9.08%.

scholarly journals Equity-Oriented Train Timetabling with Collaborative Passenger Flow Control: A Spatial Rebalance of Service on an Oversaturated Urban Rail Transit Line

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chaoqi Gong ◽  
Baohua Mao ◽  
Min Wang ◽  
Tong Zhang
Keyword(s):  
Flow Control ◽  
Programming Model ◽  
Optimal Solution ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Rail Transit ◽  
Optimization Approach ◽  
Train Timetabling ◽  
Passenger Flow ◽  
Urban Rail

On an oversaturated urban rail transit line, passengers at downstream stations have to wait for more trains until they get aboard, resulting in service imbalance problem. To improve the service quality, this paper proposes an integrated optimization approach combining the train timetabling and collaborative passenger flow control, with the aim of minimizing indicators associated with the passenger service imbalance and train loading capacity utilization. Considering train regulation constraints and passenger loading dynamics, a mixed-integer linear programming model is formulated. Based on the linear weighting technique, an iterative heuristic algorithm combining the tabu search and Gurobi solver is designed to solve the proposed model. Finally, a simple case with different-scale instances is used to verify that the proposed algorithm can obtain near-optimal solution efficiently. Moreover, a real-world case of Beijing Subway Batong Line is implemented to compare performances of the proposed approach with those under the original timetable and noncollaborative passenger flow control.

scholarly journals OPTIMIZATION ELEMENTS IN THE PLAN OF TECHNICAL COVERING OF OBJECTS IN COMMUNICATION LINES

2020 ◽  
Vol 61 (3) ◽  
pp. 4-12
Author(s):  
Vladimir A. Baboshin ◽  
◽  
Andrei K. Chernykh ◽  
Mikhail G. Iashin ◽  
Konstantin N. Savinov ◽  
...  
Keyword(s):  
Decision Support ◽  
Integer Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Mathematical Software ◽  
Rapid Convergence ◽  
The Stability ◽  
Communication Lines ◽  
Number Of Iterations

A method is proposed for solving the problem of distributing a limited integer resource of forces and means of transport support for technical cover facilities. The prospects of developing special mathematical software with the aim of improving the quality of management based on the automation of the processes of meaningful processing of information and decision support are justified. The novelty of the method is determined by the statement of the indicated problem in the form of an integer programming model. The method is characterized by the stability of the computational scheme to change the dimension of the problem, a small number of iterations and its rapid convergence to the optimal solution, which determines its effectiveness.

scholarly journals Optimizing High-Speed Railroad Timetable with Passenger and Station Service Demands: A Case Study in the Wuhan-Guangzhou Corridor

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Jin Wang ◽  
Leishan Zhou ◽  
Yixiang Yue ◽  
Jinjin Tang ◽  
Zixi Bai
Keyword(s):  
Lower Bound ◽  
High Speed ◽  
Programming Model ◽  
Optimal Solution ◽  
Travel Speed ◽  
Time Space ◽  
Proposed Model ◽  
Travel Efficiency ◽  
High Speed Railroad

This paper aims to optimize high-speed railroad timetables for a corridor. We propose an integer programming model using a time-space network-based approach to consider passenger service demands, train scheduling, and station service demands simultaneously. A modified branch-and-price algorithm is used for the computation. This algorithm solves the linear relaxation of all nodes in a branch-and-bound tree using a column generation algorithm to derive a lower-bound value (LB) and derive an upper-bound value (UB) using a rapid branching strategy. The optimal solution is derived by iteratively updating the upper- and lower-bound values. Three acceleration strategies, namely, initial solution iteration, delayed constraints, and column removal, were designed to accelerate the computation. The effectiveness and efficiency of the proposed model and algorithm were tested using Wuhan-Guangzhou high-speed railroad data. The results show that the proposed model and algorithm can quickly reduce the defined cost function by 38.2% and improve the average travel speed by 10.7 km/h, which indicates that our proposed model and algorithm can effectively improve the quality of a constructed train timetable and the travel efficiency for passengers.

scholarly journals Wind Farm Cable Connection Layout Optimization with Several Substations

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3615
Author(s):  
Adelaide Cerveira ◽  
Eduardo J. Solteiro Pires ◽  
José Baptista
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Programming Model ◽  
Optimal Solution ◽  
Wind Farms ◽  
Green Energy ◽  
Fossil Energy ◽  
Proposed Model ◽  
Short Time ◽  
Cable Connection

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.

scholarly journals Exploring the application of machine learning to the assembly line feeding problem

2021 ◽  
Author(s):  
Moretti Emilio ◽  
Tappia Elena ◽  
Limère Veronique ◽  
Melacini Marco
Keyword(s):  
Machine Learning ◽  
Assembly Line ◽  
Optimal Solution ◽  
Product Variety ◽  
Supervised Machine Learning ◽  
Assembly System ◽  
Optimization Approach ◽  
Feeding Problem ◽  
Managerial Implications ◽  
Multiple Feeding

AbstractAs a large number of companies are resorting to increased product variety and customization, a growing attention is being put on the design and management of part feeding systems. Recent works have proved the effectiveness of hybrid feeding policies, which consist in using multiple feeding policies in the same assembly system. In this context, the assembly line feeding problem (ALFP) refers to the selection of a suitable feeding policy for each part. In literature, the ALFP is addressed either by developing optimization models or by categorizing the parts and assigning these categories to policies based on some characteristics of both the parts and the assembly system. This paper presents a new approach for selecting a suitable feeding policy for each part, based on supervised machine learning. The developed approach is applied to an industrial case and its performance is compared with the one resulting from an optimization approach. The application to the industrial case allows deepening the existing trade-off between efficiency (i.e., amount of data to be collected and dedicated resources) and quality of the ALFP solution (i.e., closeness to the optimal solution), discussing the managerial implications of different ALFP solution approaches and showing the potential value stemming from machine learning application.

scholarly journals A study of transposable element-associated structural variations (TASVs) using a de novo-assembled Korean genome

2021 ◽  
Author(s):  
Seyoung Mun ◽  
Songmi Kim ◽  
Wooseok Lee ◽  
Keunsoo Kang ◽  
Thomas J. Meyer ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Genome Assembly ◽  
De Novo ◽  
Personal Genome ◽  
Human Populations ◽  
Whole Genome ◽  
Structural Variations ◽  
Insert Size ◽  
Human Genomes ◽  
Next Generation Sequencing Ngs

AbstractAdvances in next-generation sequencing (NGS) technology have made personal genome sequencing possible, and indeed, many individual human genomes have now been sequenced. Comparisons of these individual genomes have revealed substantial genomic differences between human populations as well as between individuals from closely related ethnic groups. Transposable elements (TEs) are known to be one of the major sources of these variations and act through various mechanisms, including de novo insertion, insertion-mediated deletion, and TE–TE recombination-mediated deletion. In this study, we carried out de novo whole-genome sequencing of one Korean individual (KPGP9) via multiple insert-size libraries. The de novo whole-genome assembly resulted in 31,305 scaffolds with a scaffold N50 size of 13.23 Mb. Furthermore, through computational data analysis and experimental verification, we revealed that 182 TE-associated structural variation (TASV) insertions and 89 TASV deletions contributed 64,232 bp in sequence gain and 82,772 bp in sequence loss, respectively, in the KPGP9 genome relative to the hg19 reference genome. We also verified structural differences associated with TASVs by comparative analysis with TASVs in recent genomes (AK1 and TCGA genomes) and reported their details. Here, we constructed a new Korean de novo whole-genome assembly and provide the first study, to our knowledge, focused on the identification of TASVs in an individual Korean genome. Our findings again highlight the role of TEs as a major driver of structural variations in human individual genomes.

scholarly journals Strategies for Improving Optimal Positioning of Quality Sensors in Urban Drainage Systems for Non-Conservative Contaminants

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 934
Author(s):  
Mariacrocetta Sambito ◽  
Gabriele Freni
Keyword(s):  
Treatment Plant ◽  
Optimal Solution ◽  
Monitoring Network ◽  
Computational Effort ◽  
Bayesian Optimization ◽  
Urban Drainage ◽  
Optimization Approach ◽  
Sensor Location ◽  
Contamination Source ◽  
Monitoring Point

In the urban drainage sector, the problem of polluting discharges in sewers may act on the proper functioning of the sewer system, on the wastewater treatment plant reliability and on the receiving water body preservation. Therefore, the implementation of a chemical monitoring network is necessary to promptly detect and contain the event of contamination. Sensor location is usually an optimization exercise that is based on probabilistic or black-box methods and their efficiency is usually dependent on the initial assumption made on possible eligibility of nodes to become a monitoring point. It is a common practice to establish an initial non-informative assumption by considering all network nodes to have equal possibilities to allocate a sensor. In the present study, such a common approach is compared with different initial strategies to pre-screen eligible nodes as a function of topological and hydraulic information, and non-formal 'grey' information on the most probable locations of the contamination source. Such strategies were previously compared for conservative xenobiotic contaminations and now they are compared for a more difficult identification exercise: the detection of nonconservative immanent contaminants. The strategies are applied to a Bayesian optimization approach that demonstrated to be efficient in contamination source location. The case study is the literature network of the Storm Water Management Model (SWMM) manual, Example 8. The results show that the pre-screening and ‘grey’ information are able to reduce the computational effort needed to obtain the optimal solution or, with equal computational effort, to improve location efficiency. The nature of the contamination is highly relevant, affecting monitoring efficiency, sensor location and computational efforts to reach optimality.

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