Case

2013 ◽  
Vol 4 (4) ◽  
pp. 57-74
Author(s):  
Durai Sundaramoorthi
Keyword(s):  
Operations Research ◽  
Real Life ◽  
Point System ◽  
Brand Name ◽  
User Friendliness ◽  
Binary Integer Programming ◽  
Undergraduate Level ◽  
Premier League ◽  
Science Operations ◽  
Selection Of

Cricket is a bat-and-ball team sport, played by two teams with eleven players on each side. Recently, a new format of cricket called ‘Twenty20’ (T20) was introduced, which has increased the excitement, fan following, and business opportunities in cricket. In 2008, Indian Premier League (IPL) was created with eight city-based franchises. Two more franchises were added in 2010. The focus of this case is on the selection of the playing eleven for the team Kolkata Knight Riders (KKR), the most valued brand name among IPL franchises. Thirty five players were on the KKR team roster in the first two editions of the IPL. Unlike many other sports, the playing eleven cannot be changed in a cricket game once the game starts. The case aims to strengthen students’ ability to mathematically formulate a real life “yes-or-no” type decision. Binary Integer Programming (BIP) is a suitable choice for modeling “yes-or-no” type decisions. The case, if provided with International Cricket Council (ICC) rankings data and in-house point system, will be appropriate for an undergraduate level management science/operations research class. The same case will be suitable at graduate level, if students are expected to gather ICC rankings data and build in-house point system. There are competing constraints that would lead to discussions about infeasibility. The case also points out the importance of interpretation of the solution and user friendliness of the model from an end user’s perspective.

Optimization of The Best Line-up in Football using Binary Integer Programming Model

2020 ◽  
Vol 1 (3) ◽  
pp. 114-122
Author(s):  
Mahrudinda . ◽  
Sudrajat Supian ◽  
Subiyanto . ◽  
Diah Chaerani
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Binary Integer Programming ◽  
Optimum Result ◽  
Premier League ◽  
Maximum Value ◽  
Football Team ◽  
Selection Of Variables ◽  
English Premier League ◽  
Selection Of

This paper aims to find the formation with the best line-up of the Liverpool FC football team in the English Premier League in the 2020/2021 season. Researchers used binary integer programming (BIP) modeling to determine optimum solutions. The data used for this optimization is the rating value of the players recorded in the performance data from the previous matches. The optimum result of this problem is the selection of variables that are valued at 1, namely {x_1, x_4, x_6, x_8, x_21, x_28, x_34, x_37, and x_39} for formations 4-3-3 with a maximum value of 82.47, and variables {x_1, x_6, x_7, x_8, x_11, x_14, x_16, x_29, x_31, x_32, andx_42} for 4-2-3-1 formations with a maximum value of 80.04. The 4-3-3 formation is more effective because it has a higher maximum rating than the 4-2-3-1 formation.  4-3-3 formation is an attacking formation with a higher intensity of attack and faster than  4-2-3-1 formation that tends to defend moderately.

scholarly journals Optimization of The Best Line-up in Football using Binary Integer Programming Model

2020 ◽  
Vol 1 (3) ◽  
pp. 114-122
Author(s):  
Mahrudinda Mahrudinda ◽  
Sudrajat Supian ◽  
Subiyanto Subiyanto ◽  
Diah Chaerani
Keyword(s):  
Integer Programming ◽  
Programming Model ◽  
Binary Integer Programming ◽  
Optimum Result ◽  
Premier League ◽  
Maximum Value ◽  
Football Team ◽  
Selection Of Variables ◽  
English Premier League ◽  
Selection Of

This paper aims to find the formation with the best line-up of the Liverpool FC football team in the English Premier League in the 2020/2021 season. Researchers used binary integer programming (BIP) modeling to determine optimum solutions. The data used for this optimization is the rating value of the players recorded in the performance data from the previous matches. The optimum result of this problem is the selection of variables that are valued at 1, namely {𝑥1,𝑥4,𝑥6,𝑥8,𝑥11,𝑥18,𝑥21,𝑥28,𝑥34,𝑥37,dan 𝑥39 } for formations 4-3-3 with a maximum value of 82.47, and variables {𝑥1,𝑥6,𝑥7,𝑥8,𝑥11,𝑥14,𝑥16,𝑥29,𝑥31,𝑥32, dan 𝑥42 } for 4-2-3-1 formations with a maximum value of 80.04. The 4-3-3 formation is more effective because it has a higher maximum rating than the 4-2-3-1 formation. 4-3-3 formation is an attacking formation with a higher intensity of attack and faster than 4-2-3-1 formation that tends to defend moderately.

scholarly journals Hybridization of ring theory-based evolutionary algorithm and particle swarm optimization to solve class imbalance problem

2021 ◽  
Author(s):  
Sayan Surya Shaw ◽  
Shameem Ahmed ◽  
Samir Malakar ◽  
Laura Garcia-Hernandez ◽  
Ajith Abraham ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Real Life ◽  
Class Imbalance ◽  
Ring Theory ◽  
Class Imbalance Problem ◽  
Minority Class ◽  
Swarm Optimization ◽  
Imbalance Problem ◽  
Representative Samples ◽  
Selection Of

AbstractMany real-life datasets are imbalanced in nature, which implies that the number of samples present in one class (minority class) is exceptionally less compared to the number of samples found in the other class (majority class). Hence, if we directly fit these datasets to a standard classifier for training, then it often overlooks the minority class samples while estimating class separating hyperplane(s) and as a result of that it missclassifies the minority class samples. To solve this problem, over the years, many researchers have followed different approaches. However the selection of the true representative samples from the majority class is still considered as an open research problem. A better solution for this problem would be helpful in many applications like fraud detection, disease prediction and text classification. Also, the recent studies show that it needs not only analyzing disproportion between classes, but also other difficulties rooted in the nature of different data and thereby it needs more flexible, self-adaptable, computationally efficient and real-time method for selection of majority class samples without loosing much of important data from it. Keeping this fact in mind, we have proposed a hybrid model constituting Particle Swarm Optimization (PSO), a popular swarm intelligence-based meta-heuristic algorithm, and Ring Theory (RT)-based Evolutionary Algorithm (RTEA), a recently proposed physics-based meta-heuristic algorithm. We have named the algorithm as RT-based PSO or in short RTPSO. RTPSO can select the most representative samples from the majority class as it takes advantage of the efficient exploration and the exploitation phases of its parent algorithms for strengthening the search process. We have used AdaBoost classifier to observe the final classification results of our model. The effectiveness of our proposed method has been evaluated on 15 standard real-life datasets having low to extreme imbalance ratio. The performance of the RTPSO has been compared with PSO, RTEA and other standard undersampling methods. The obtained results demonstrate the superiority of RTPSO over state-of-the-art class imbalance problem-solvers considered here for comparison. The source code of this work is available in https://github.com/Sayansurya/RTPSO_Class_imbalance.

scholarly journals Extending QGroundControl for Automated Mission Planning of UAVs

Sensors ◽  
2018 ◽  
Vol 18 (7) ◽  
pp. 2339 ◽  
Author(s):  
Cristian Ramirez-Atencia ◽  
David Camacho
Keyword(s):  
Flight Control ◽  
Low Cost ◽  
Real Life ◽  
Mission Planning ◽  
Human Computer Interface ◽  
Simulation Environment ◽  
Test Bed ◽  
Multiple Vehicles ◽  
Operator Workload ◽  
Selection Of

Unmanned Aerial Vehicles (UAVs) have become very popular in the last decade due to some advantages such as strong terrain adaptation, low cost, zero casualties, and so on. One of the most interesting advances in this field is the automation of mission planning (task allocation) and real-time replanning, which are highly useful to increase the autonomy of the vehicle and reduce the operator workload. These automated mission planning and replanning systems require a Human Computer Interface (HCI) that facilitates the visualization and selection of plans that will be executed by the vehicles. In addition, most missions should be assessed before their real-life execution. This paper extends QGroundControl, an open-source simulation environment for flight control of multiple vehicles, by adding a mission designer that permits the operator to build complex missions with tasks and other scenario items; an interface for automated mission planning and replanning, which works as a test bed for different algorithms, and a Decision Support System (DSS) that helps the operator in the selection of the plan. In this work, a complete guide of these systems and some practical use cases are provided

Development and Implementation of Shape Comparison of 3D CAD Models

2009 ◽  
Author(s):  
Sagar Chowdhury ◽  
Zahed Siddique
Keyword(s):  
Computer Hardware ◽  
Efficient Design ◽  
User Friendliness ◽  
Specialized Knowledge ◽  
3D Cad ◽  
Large Databases ◽  
Modeling Software ◽  
Cad Models ◽  
Near Future ◽  
Selection Of

With the advancements of 3D modeling software, the use of CAD in design has become a standard practice. In recent years development in computer hardware and improvements in user friendliness of the CAD software has allowed designers to quickly and easily modify the CAD models. This modification capability allows CAD to be an integral part of the design process. Due to the increase in global competition, companies have become increasingly interested in fast and efficient design processes. One way to achieve improved efficiency is through better collaboration among designers working in common or similar projects and disciplines. A large design problem often requires specialized knowledge from several fields. Collaboration among the designers from these fields will ensure efficient design. Interaction among the designers can prevent redesign of similar components/subsystems, which requires the ability to share their designs. With the increase of collaboration, designers can now get access to large databases of 3D CAD models. But the challenge lies in search capabilities to identify common models from a large database. These considerations suggest that in the near future a challenge in 3D CAD industry will be how to find models of similar components and products. This paper presents an approach and its implementation to measure the similarity among a number of CAD models. The approach is based on the extraction and organization of information from the CAD models, which is followed by the suitable selection of commonality index and calculation of the commonality among a set of CAD models. A set of Vacuum cleaners are modeled and then compared to demonstrate the application of the approach.

scholarly journals Evolutionary Multitasking-Based Multiobjective Optimization Algorithm for Channel Selection in Hybrid Brain Computer Interfacing Systems

2021 ◽  
Vol 15 ◽  
Author(s):  
Tianyu Liu ◽  
Zhixiong Xu ◽  
Lei Cao ◽  
Guowei Tan
Keyword(s):  
Multiobjective Optimization ◽  
Real Life ◽  
Channel Selection ◽  
Research Field ◽  
Neural Engineering ◽  
Computer Interfaces ◽  
Classification Tasks ◽  
Optimization Methodology ◽  
Brain Computer Interfacing ◽  
Selection Of

Hybrid-modality brain-computer Interfaces (BCIs), which combine motor imagery (MI) bio-signals and steady-state visual evoked potentials (SSVEPs), has attracted wide attention in the research field of neural engineering. The number of channels should be as small as possible for real-life applications. However, most of recent works about channel selection only focus on either the performance of classification task or the effectiveness of device control. Few works conduct channel selection for MI and SSVEP classification tasks simultaneously. In this paper, a multitasking-based multiobjective evolutionary algorithm (EMMOA) was proposed to select appropriate channels for these two classification tasks at the same time. Moreover, a two-stage framework was introduced to balance the number of selected channels and the classification accuracy in the proposed algorithm. The experimental results verified the feasibility of multiobjective optimization methodology for channel selection of hybrid BCI tasks.

scholarly journals Exploring young students creativity: the effect of model eliciting activities

2014 ◽  
Vol 8 (2) ◽  
pp. 51-59
Author(s):  
Talya Gilat ◽  
Miriam Amit
Keyword(s):  
Mathematical Modeling ◽  
Creative Thinking ◽  
Real Life ◽  
Model Eliciting Activities ◽  
Thinking Processes ◽  
Young Students ◽  
Selection Of

The aim of this paper is to show how engaging students in real-life mathematical situations can stimulate their mathematical creative thinking. We analyzed the mathematical modeling of two girls, aged 10 and 13 years, as they worked on an authentic task involving the selection of a track team. The girls displayed several modeling cycles that revealed their thinking processes, as well as cognitive and affective features that may serve as the foundation for a methodology that uses model-eliciting activities to promote the mathematical creative process.Exploración de la creatividad de jóvenes estudiantes: el efecto de actividades que suscitan modelosEl objetivo de este artículo es mostrar cómo involucrar a los estudiantes en situaciones matemáticas de la vida real puede estimular su pensamiento matemático creativo. Analizamos la modelización matemática de dos chicas, de 10 y 13 años, cuando trabajaban en una tarea auténtica que involucraba la selección de un equipo de atletismo. Las chicas mostraron varios ciclos de modelización que revelaron sus procesos de pensamiento, así como las características cognitivas y afectivas que pueden servir como fundamento para una metodología que usa actividades que suscitan modelos para promover los procesos matemáticos creativos.Handle: http://hdl.handle.net/10481/29578Nº de citas en SCOPUS (2017): 1 (Citas de 2º orden, 0)

Sign in / Sign up

Export Citation Format

Share Document