40 research outputs found

    Recipes for Building the Dual of Conic Optimization Problem

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    Building the dual of the primal problem of Conic Optimization (CO) isa very important step to make the ¯nding optimal solution. In many cases a givenproblem does not have the simple structure of CO problem (i.e., minimizing a linearfunction over an intersection between a±ne space and convex cones) but there areseveral conic constraints and sometimes also equality constraints. In this paper wedeal with the question how to form the dual problem in such cases. We discuss theanswer by considering several conic constraints with or without equality constraints.The recipes for building the dual of such cases is formed in standard matrix forms,such that it can be used easily on the numerical experiment. Special attention isgiven to dual development of special classes of CO problems, i.e., conic quadraticand semide¯nite problems. In this paper, we also brie°y present some preliminariestheory on CO as an introduction to the main topic.DOI : http://dx.doi.org/10.22342/jims.16.1.28.9-2

    Systematic Literature Review Robust Graph Coloring on Electric Circuit Problems

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    Graph Coloring Problem (GCP) is the assignment of colors to certain elements in a graph based on certain constraints. GCP is used by assigning a color label to each node with neighboring nodes assigned a different color and the minimum number of colors used. Based on this, GCP can be drawn into an optimization problem that is to minimize the colors used. Optimization problems in graph coloring can occur due to uncertainty in the use of colors to be used, so it can be assumed that there is an uncertainty in the number of colored vertices. One of the mathematical optimization methods in the presence of uncertainty is Robust Optimization (RO). RO is a modeling methodology combined with computational tools to process optimization problems with uncertain data and only some data for which certainty is known. This paper will review research on Robust GCP with model validation to be applied to electrical circuit problems using a systematic review of the literature. A systematic literature review was carried out using the Preferred Reporting Items for Systematic reviews and Meta Analysis (PRISMA) method. The keywords used in this study were used to search for articles related to this research using a database. Based on the results of the search for articles obtained from PRISMA and Bibliometric R Software, it was found that there was a relationship between the keywords Robust Optimization and Graph Coloring, this means that at least there is at least one researcher who has studied the problem. However, the Electricity keyword has no relation to the other two keywords, so that a gap is obtained and it is possible if the research has not been studied and discussed by other researchers. Based on the results of this study, it is hoped that it can be used as a consideration and a better solution to solve optimization problems

    Solving Uncertain Online Shopping Problem With Discounts Using Robust Counterpart Methodology

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    Online Shopping is a phenomenon that is growing rapidly at this time and consumers are an important element in the buying and selling competition in the market and consumers who make a difffference in determining the profifits of the sellers. This research discusses the problem of online shopping using the Robust Optimization method. Robust Optimization Method is a process to get optimal results with an uncertainty. Based on the demand model to optimize the buying price, an Integer Linear Programming model with discount functions is built which will be converted into Robust Optimization. In this study also used a tool that is the Maple application in the numerical calculation process

    Robust Coloring Optimization Model on Electricity Circuit Problems

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    The Graph Coloring Problem (GCP) is assigning different colors to certain elements in a graph based on certain constraints and using a minimum number of colors. GCP can be drawn into optimization problems, namely the problem of minimizing the color used together with the uncertainty in using the color used, so it can be assumed that there is an uncertainty in the number of colored vertices. One of the mathematical optimization techniques in dealing with uncertainty is Robust Optimization (RO) combined with computational tools. This article describes a robust GCP using the Polyhedral Uncertainty Theorem and model validation for electrical circuit problems. The form of an electrical circuit color chart consists of corners (components) and edges (wires or conductors). The results obtained are up to 3 colors for the optimization model for graph coloring problems and up to 5 colors for robust optimization models for graph coloring problems. The results obtained with robust optimization show more colors because the results contain uncertainty. When RO GCP is applied to an electrical circuit, the model is used to place the electrical components in the correct path so that the electrical components do not collide with each other

    RANCANGAN MODEL SIMULASI ANTRIAN UNTUK MENGURANGI KEMACETAN KENDARAAN DI PELABUHAN MERAK BANTEN

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    Transportasi yang tidak efisien akan menyebabkan kerugian bagi masyarakat pengguna transportasi, diantaranya kemacetan, kecelakaan, dan hambatan mobilitas. Hambatan-hambatan tersebut mengakibat besarnya ongkos yang harus ditanggung oleh masyarakat pengguna dan lebih-lebih ongkos kehilangan kepercayaan. Pada paper ini akan dibahas tentang model simulasi sistem antrian di Pelabuhan Penyeberangan Merak dengan tujuan untuk mengurangi timbulnya antrian yang menyebabkan kemacetan. Kata Kunci : sistem antrian, transportasi, model, pelabuhan, distribusi, simulasi

    KECERDASAN EMOSIONAL DAN AGGRESSIVE DRIVING PADA PENGEMUDI SEPEDA MOTOR

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    Penelitian ini dilakukan untuk mengetahui hubungan kecerdasan emosional dengan aggressive driving pada pengemudi sepeda motor. Penelitian dilakukan dengan metode kuantitatif. Teknik sampling yang digunakan adalah teknik non probability sampling yaitu incidental sampling. Alat ukur kecerdasan emosional yang digunakan adalah skala yang diadaptasi dari M. Zainul Asyikin, sedangkan alat ukur aggressive drivingyang digunakan adalah skala yang diadaptasi dari Nadiyya Utami. Reliabilitas pada skala kecerdasan emosional adalah sebesar 0,88 dan reliabilitas pada skala aggressive driving adalahsebesar 0,92. Responden final yang diperoleh sebanyak 85 responden. Hasil penelitian ini menunjukkan adanya hubungan yang signifikan antara kecerdasan emosional dan aggressive driving dengan hubungan keduanya bersifat negatif, yaitu jika skor kecerdasan emosional tinggi maka skor aggressive driving rendah, sedangkan jika skor kecerdasan emosional rendah maka semakin skor aggressive driving rendah dengan nilai r= -0,286; p = 0,008< 0,05 (signifikan). This study was conducted to identify the relationship of emotional intelligence and aggressive driving on motorcycle rider. The study was done by quantitative method. The technique used in this study was non-probability technique and using incidental sampling technique. The instrument for emotional intelligence adapted from M. Zainul Asyikin and the instrument for aggressive driving adapted from Nadiyya Utami. The reliability score from emotional intelligence scale is 0,88 and the reliability fromaggressive driving scale is 0,92. There are 85 final respondents in this study. The result from this study shows there is a significant relationship between emotional intelligence and aggressive driving, and the relationship is negative, which means higher score on emotional intelligence, thus lower score on aggressive driving, and so do the opposite, with r value = -0,286; p value = 0,008 < 0,05 (significant)

    Systematic Literature Review on Troubleshooting Delivery of Production Product Using n-Vehicle with Vogel Total Difference Approach Method

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    The product delivery strategy using n-vehicle is the application of optimization for transportation problems. The product delivery strategy using n-vehicle is useful for minimizing the shipping costs of a company’s production. This article presents a peer-reviewed bibliometric analysis based on the topic of production delivery strategies using n-vehicle. Overall, there are 91 articles from the Dimension, Science Direct, and Google Scholar databases in 2013-2021 that use the topic of production delivery strategies using n-vehicle based on the keywords ”Capacitated transportation problem” and ”cost” and ”vehicle” and” optimal solutions”. The researcher presents the relationship of each cited article so that it can show the collaboration of all the cited articles. This article aims to generate and review analysis results through Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) and State of The Art. Bibliometric analysis, PRISMA, and State of The Art show how the development of research on production delivery strategies using n-vehicle. So, it can produce suggestions in conducting the latest research related to studies on the topic of production delivery strategies using n-vehicle. Based on PRISMA’s analysis, 91 articles were obtained, of those 91 articles, 11 articles discussed the strategy of delivering production products using n-vehicle in depth. The State of The Art also shows how the development of research on production delivery strategies using n-vehicle is developing. It can be seen that apart from the classical method, other methods are also emerging to solve transportation problems. One of them is Vogel Total Difference Approach Method (VTDM)

    Information diffusion model with homogeneous continuous time Markov chain on Indonesian Twitter users

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    In this paper, a homogeneous continuous time Markov chain (CTMC) is used to model information diffusion or dissemination, also to determine influencers on Twitter dynamically. The tweeting process can be modeled with a homogeneous CTMC since the properties of Markov chains are fulfilled. In this case, the tweets that are received by followers only depend on the tweets from the previous followers. Knowledge Discovery in Database (KDD) in Data Mining is used to be research methodology including pre-processing, data mining process using homogeneous CTMC, and post-processing to get the influencers using visualization that predicts the number of affected users. We assume the number of affected users follows a logarithmic function. Our study examines the Indonesian Twitter data users with tweets about covid19 vaccination resulted in dynamic influencer rankings over time. From these results, it can also be seen that the users with the highest number of followers are not necessarily the top influencer.publishedVersio

    Robust Optimization Model for Internet Shopping Online Problems with Endorsement Costs in the Fashion Industry

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    Online business is a business activity carried out via the internet or digitally. Buying, selling, and advertising are done online through e-commerce, social media, or online shops. The products offered vary, including services, food, household needs, and fashion. Selling online is not limited by time and distance, and consumers can obtain information about products and services that can influence their decisions. At the same time, sellers also have the opportunity to advertise their products in a broader range by making endorsements. An endorsement is a form of advertising using well-known figures who are recognized, trusted, and respected by people. In this thesis, a model for optimizing the problem of online internet shopping with endorsement fees is formulated. This optimization model aims to maximize the profits gained by sellers in marketing their products online. In marketing products, there is uncertainty in the number of requests. To overcome this uncertainty, an approach is needed that can handle this uncertainty, namely Robust optimization. The Robust optimization model is solved using the polyhedral uncertainty set approach, resulting in a computationally tractable optimal solution.   Keywords: internet shopping online; endorsement costs; robust optimization

    Determining Flood Protection Strategy with Uncertain Parameter Using Adjustable Robust Counterpart Methodology

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    Flooding is a natural disaster that often occurs, it is not surprising that floods are one of the problems that must be resolved in various countries, one of which is Indonesia. Flood is very detrimental to the public because the impact could be the loss of material and non-material. A flood protection system is needed and must be managed properly. This aims in management of flood protection systems often requires efficient cost control strategies that are the lowest possible long-term costs, but still meets the flood protection standards imposed by regulators in all plans. In this paper a flood protection strategy is modeled using Adjustable Robust Optimization. In this approach, there are two kinds of variables that must be decided, i.e., adjustable and non-adjustable variables. A numerical simulation is presented using Scilab Software. Keywords: Flood Protection Strategy, Uncertainty, Adjustable Robust Optimization, Scilab Software
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