scholarly journals VNS-BASED ALGORITHMS FOR THE CENTROID-BASED CLUSTERING PROBLEM

2019 ◽  
pp. 957 ◽  
Author(s):  
Ivan P. Rozhnov ◽  
Victor I. Orlov ◽  
Lev A. Kazakovtsev
Keyword(s):  
Objective Function Value ◽  
Heuristic Method ◽  
Problem Formulation ◽  
Greedy Heuristic ◽  
Analysis Problem ◽  
Clustering Problem ◽  
First Results ◽  
Automatic Grouping ◽  
New Algorithms ◽  
Stable Result

The k-means algorithm with the corresponding problem formulation is one of the first methods that researchers use when solving a new automatic grouping (clus-tering) problem. Its improvement, modification and combination with other algorithms are described in the works of many researchers. In this research, we propose new al-gorithms of the Greedy Heuristic Method, which use an idea of the search in variable neighborhoods for solving the classical cluster analysis problem, and allows us to obtain a more accurate and stable result of solving in comparison with the known algorithms. Our computational experiments show that the new algorithms allow us to obtain re-sults with better values of the objective function value (sum of squared distances) in comparison with classical algorithms such as k-means, j-means and genetic algorithms on various practically important datasets. In addition, we present the first results for the GPU realization of the Greedy Heuristic Method.

scholarly journals Training on ant sugar production to increase people's income in Ba'ka Village, Enrekang

2021 ◽  
Vol 6 (7) ◽  
pp. 1133-1138
Author(s):  
Irman Syarif ◽  
Agusriandi Agusriandi ◽  
Elihami Elihami ◽  
Ita Sarmita Samad ◽  
Sry Wahyuni R
Keyword(s):  
Community Service ◽  
Program Implementation ◽  
Problem Formulation ◽  
Needs Analysis ◽  
Sugar Production ◽  
Analysis Problem ◽  
Work Program ◽  
The People ◽  
Service Activity ◽  
Palm Sugar

Most of the people of Ba'ka Village are conventional palm sugar farmers whose whose selling prices are cheap. The purpose of this service is to provide innovation in palm sugar into ant sugar. Through training in making ant sugar, it is hoped that it can increase people's income. The stages of community service include needs analysis, problem formulation, work program formulation, and work program implementation, and evaluation. This service activity produces ant sugar products that are packaged in a modern way. Ant sugar products can attract consumers because they are more durable, hygienic, and practical.

COMPARATIVE ANALYSIS OF THE K-STANDARDS ALGORITHM APPLICATION FOR THE CLUSTERING PROBLEM

2021 ◽  
pp. 10-14
Author(s):  
Н.Л. Резова ◽  
И.П. Рожнов ◽  
А.А. Истомина
Keyword(s):  
Comparative Analysis ◽  
Clustering Problem ◽  
Automatic Grouping

В статье рассматривается применение алгоритма k-эталонов для задачи кластеризации на примере производственных партий электрорадиоизделий, сделан вывод о качестве работы алгоритма k-эталонов и целесообразности его использования при решении задач автоматической группировки продукции. The article discusses the application of the k-standards algorithm for the clustering problem on the example of production batches of electrical radio products, a conclusion was made about the quality of the k-standards algorithm and the expediency of its use in automatic grouping problems solving.

Knowledge Composition for Efficient Analysis Problem Formulation: Part 2 — Approach and Analysis Meta-Model

2007 ◽  
Author(s):  
Manas Bajaj ◽  
Russell S. Peak ◽  
Christiaan J. J. Paredis
Keyword(s):  
Model Transformation ◽  
Gap Analysis ◽  
Cost Effective ◽  
Building Blocks ◽  
Problem Formulation ◽  
Analysis Model ◽  
Product Model ◽  
Analysis Problem ◽  
Meta Model ◽  
Analysis Models

In Part 1 we presented technical background and a gap analysis leading to the identification of five requirements for a methodology for efficient formulation of analysis problems for VTMB design alternatives. These requirements are founded on (a) abstraction of analysis knowledge as modular, reusable, computer-interpretable, analyst-intelligible building blocks, and (b) automated creation, reconfiguration, and verification of analysis models. In this paper (Part 2), we present an example scenario to overview the Knowledge Composition Methodology (KCM) that is aimed at satisfying these requirements. The methodology is founded on analysis knowledge building blocks and a model transformation process based on graph transformations. With KCM an analyst may automatically compose an analysis model from a design model and these building blocks. In this paper, we focus on the analysis knowledge component of this methodology (illustrated for structural and thermal disciplines), and describe four dimensions of analysis knowledge. Using these dimensions, we develop a decision template for analysts to create specifications for analysis models. Analysis models can be automatically created from a given specification using model transformation techniques (not described in this paper). We leverage the notion of choices and decisions to (a) define primitive and complex building blocks of analysis knowledge, and (b) formalize an analysis meta-model that represents the structure of analysis models. We also relate this analysis meta-model to the NIST Core Product Model (CPM2). The envisioned methodology impact is a formal and systems-oriented foundational approach for analysis problem formulation that is time- and cost-effective.

scholarly journals Network Coding for Backhaul Offloading in D2D Cooperative Fog Data Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ben Quinton ◽  
Neda Aboutorab
Keyword(s):  
Network Coding ◽  
Heuristic Algorithm ◽  
Graph Model ◽  
Optimal Solution ◽  
Problem Formulation ◽  
Full Duplex ◽  
Greedy Heuristic ◽  
Data Networks ◽  
Distributed Data ◽  
Stochastic Shortest Path

Future distributed data networks are expected to be assisted by users cooperation and coding schemes. Given the explosive increase in the end-users’ demand for download of the content from the servers, in this paper, the implementation of instantly decodable network coding (IDNC) is considered in full-duplex device-to-device (D2D) cooperative fog data networks. In particular, this paper is concerned with designing efficient transmission schemes to offload traffic from the expensive backhaul of network servers by employing IDNC and users cooperation. The generalized framework where users send request for multiple packets and the transmissions are subject to erasure is considered. The optimal problem formulation is presented using the stochastic shortest path (SSP) technique over the IDNC graph with induced subgraphs. However, as the optimal solution suffers from the intractability of being NP-hard, it is not suitable for real-time communications. The complexity of the problem is addressed by presenting a greedy heuristic algorithm used over the proposed graph model. The paper shows that by implementing IDNC in a full-duplex cooperative D2D network model significant reduction in the number of downloads required from the servers can be achieved, which will result in offloading of the backhaul servers and thus saving valuable servers’ resources. It is also shown that the performance of the proposed heuristic algorithm is very close to the optimal solution with much lower computational complexity.

scholarly journals Multi-Robot Routing Problem with Min–Max Objective

Robotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 122
Author(s):  
Jennifer David ◽  
Thorsteinn Rögnvaldsson
Keyword(s):  
Simulated Annealing ◽  
Comparative Study ◽  
Bipartite Graph ◽  
Real World ◽  
Heuristic Method ◽  
Problem Formulation ◽  
Permutation Matrix ◽  
Routing Problem ◽  
Research Communities ◽  
Multi Robot

In this paper, we study the “Multi-Robot Routing problem” with min–max objective (MRR-MM) in detail. It involves the assignment of sequentially ordered tasks to robots such that the maximum cost of the slowest robot is minimized. The problem description, the different types of formulations, and the methods used across various research communities are discussed in this paper. We propose a new problem formulation by treating this problem as a bipartite graph with a permutation matrix to solve it. A comparative study is done between three methods: Stochastic simulated annealing, deterministic mean-field annealing, and a heuristic-based graph search method. Each method is investigated in detail with several data sets (simulation and real-world), and the results are analysed and compared with respect to scalability, computational complexity, optimality, and its application to real-world scenarios. The paper shows that the heuristic method produces results very quickly with good scalability. However, the solution quality is sub-optimal. On the other hand, when optimal or near-optimal results are required with considerable computational resources, the simulated annealing method proves to be more efficient. However, the results show that the optimal choice of algorithm depends on the dataset size and the available computational budget. The contribution of the paper is three-fold: We study the MRR-MM problem in detail across various research communities. This study also shows the lack of inter-research terminology that has led to different names for the same problem. Secondly, formulating the task allocation problem as a permutation matrix formulation (bipartite graph) has opened up new approaches to solve this problem. Thirdly, we applied our problem formulation to three different methods and conducted a detailed comparative study using real-world and simulation data.

New algorithms for solving the fuzzy clustering problem

1994 ◽  
Vol 27 (3) ◽  
pp. 421-428 ◽  
Author(s):  
Mohamed S. Kamel ◽  
Shokri Z. Selim
Keyword(s):  
Fuzzy Clustering ◽  
Clustering Problem ◽  
New Algorithms

scholarly journals MODEL DEVELOPMENT OF RIDE SPLITTING SERVICE WITH RESOURCE SHARING SCHEME ON RIDE SOURCING (ONLINE TAXI) SERVICES IN JAKARTA

2021 ◽  
Vol 22 (1) ◽  
pp. 175-190
Author(s):  
Helen Burhan ◽  
Sutanto Soehodho ◽  
Nahry Nahry
Keyword(s):  
Resource Sharing ◽  
Model Development ◽  
Heuristic Method ◽  
Profit Sharing ◽  
Greedy Heuristic ◽  
Similar Time ◽  
Bipartite Matching ◽  
Sharing Scheme ◽  
Taxi Service ◽  
On The Road

ABSTRACT:  This study aims to solve the increasing number of vehicles for ride-sourcing or online taxi service on the road and the operational issues in those services by developing an optimization model of ride-splitting services in the online taxi with a resource sharing (sharing platform) scheme. Ride-splitting service is a ride-sourcing service where one vehicle can serve two or more request customers at a similar time. Meanwhile, the resource-sharing scheme interlinks drivers from different platforms in providing services to the customers. That is, a driver from platform X can serve customers from platform Y and vice versa, with a predetermined profit sharing.  We formulate the optimization problem as a new modified weighted bipartite matching and solve the problem using a greedy heuristic method.  Based on the simulation, the proposed model can generate higher overall profit for all vehicles serving passengers, use fewer vehicles, and lower passengers’waiting time. ABSTRAK:  Kajian ini bertujuan menyelesaikan­ jumlah penambahan kenderaan angkutan-berpusat atau servis teksi dalam talian di atas jalan raya dan isu operasi dalam perkhidmatan dengan membangunkan model pengoptimuman pada servis angkutan-pecahan bagi teksi dalam talian dengan skim perkongsian sumber (platform bersama). Servis angkutan-pecahan adalah servis angkutan-berpusat di mana satu kenderaan menyediakan perkhidmatan kepada dua atau lebih permintaan pengguna pada satu-satu masa. Manakala, perkongsian sumber menghubungkan pemandu dengan platform berlainan dalam menyediakan servis untuk penumpang. Iaitu, pemandu platform X boleh mengangkut penumpang platform Y dan sebaliknya, dengan menentukan terlebih dahulu keuntungan bersama. Kajian ini diformulasi dengan pengoptimuman masalah sebagai perubahan terbaru dalam menilai kesesuian kedua-dua pihak dan menyelesaikan masalah menggunakan kaedah heuristik rakus. Berdasarkan simulasi ini, model yang dicadangkan dapat menghasilkan keuntungan keseluruhan lebih tinggi bagi semua kenderaan perkhidmatan, dengan mengurangkan jumlah kenderaan dan masa menunggu penumpang.    

scholarly journals Three-Dimensional Genetic Algorithm for the Kirkman's Schoolgirl Problem

MENDEL ◽  
2018 ◽  
Vol 24 (1) ◽  
pp. 25-30
Author(s):  
Jan Merta ◽  
Tomas Brandejsky
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Heuristic Method ◽  
Three Dimensional ◽  
Genetic Operators ◽  
Convergence Of An Algorithm ◽  
Literature Overview ◽  
Simple Heuristic ◽  
First Results ◽  
Incorrect Solution

This paper focuses on the possibilities of multidimensional genetic algorithms and relevant genetic operators. After the literature overview we used a three-dimensional genetic algorithm to solve a combinatorial task called Kirkman’s Schoolgirl Problem. The first results were not good, but we improved convergence of an algorithm by adding more genetic operators. We also used problem dependent mutation, where we tried to repair the incorrect solution by using the simple heuristic method. Finally, we got a solid number of correct solutions, but we know there is enough room for other improvements.

Enhancing Range of Transport in Optical Tweezers Assisted Microfluidic Chambers Using Automated Stage Motion

2013 ◽  
Author(s):  
Sagar Chowdhury ◽  
Petr Švec ◽  
Atul Thakur ◽  
Chenlu Wang ◽  
Wolfgang Losert ◽  
...  
Keyword(s):  
Optical Tweezers ◽  
High Speed ◽  
Optical Trap ◽  
Heuristic Method ◽  
Optical Traps ◽  
Greedy Heuristic ◽  
Long Distance ◽  
Microfluidic Chamber ◽  
Planning Approach ◽  
Cell Ensemble

In this paper, we present a planning approach for automated high-speed transport of cells over large distances inside an Optical Tweezers (OT) assisted microfluidic chamber. The transport is performed in three steps that combine the optical trap and motorized stage motions. This includes optical trapping and transporting the cells to form a desired cell-ensemble that is suitable for a long distance transport, automatically moving the motorized stage to transport the cell-ensemble over a large distance while avoiding static obstacles, and distributing the cells from the ensemble to the desired locations using OT. The speeds of optical traps and the motorized stage are determined by modeling the motion of the particle under the influence of optical trap. The desired cell-ensemble is automatically determined based on the geometry of the microfluidic chamber. We have developed a greedy heuristic method for optimal selection of the initial and the final location of the cell-ensemble to minimize the overall transport time while satisfying the constraints of the OT workspace. We have discussed the computational complexity of the developed method and compared it with exhaustive combinatorial search. The approach is particularly useful in applications where cells are needed to be rapidly distributed inside a microfluidic chamber. We show the capability of our planning approach using physical experiments.

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