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Abstrak :
Pergerakan respirasi saat treatment radioterapi tumor dalam toraks seperti pada kasus Non-small Cell Lung Cancer (NSCLC) merupakan salah satu hal yang perlu dipertimbangkan dalam keakurasian dosis. Pergerakan tersebut menghasilkan ketidakpastian posisi target pada saat treatment radiasi yang dapat mengakibatkan adanya kekurangan dosis akibat adanya dose blurring dan interplay effect. Penelitian terdahulu membuktikan bahwa penambahan margin internal pada PTV dapat mengurangi perbedaan dosis perencanaan dengan dosis terukur. Penelitian ini bertujuan untuk mempelajari pengaruh metode optimasi robust yang memperhitungkan ketidakpastian posisi relatif terhadap volume target dalam perencanaan radioterapi dan perbandingannya dengan metode konvensional yang dilakukan pada fantom toraks dinamik in-house. Penggunaan metode ini meningkatkan nilai konformitas dosis pada teknik IMRT dan VMAT, meningkatkan uniformitas dosis pada teknik VMAT, namun mengurangi kecuraman dosis fall-off perencanaan. Metode ini meningkatkan nilai dosis target pada perencanaan IMRT konvensional dari rerata 199,63 cGy menjadi 200,43; 206,26; dan 204,20 cGy untuk ketidakpastian 5 mm, 10 mm, dan 15 mm, tetapi menurunkan dosis target pada perencanaan VMAT konvensional dari rerata 201,59 cGy menjadi 198,84; 199,05; dan 199,06 cGy untuk ketidakpastian 5 mm, 10 mm, dan 15 mm. Metode ini juga meningkatkan dosis OAR di area terdekat target dan menurunkan dosis di area lainnya pada teknik IMRT, namun hampir seluruh area OAR mendapatkan peningkatan dosis pada teknik VMAT.

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Respiration movement, when treating radiotherapy to the tumor in the thorax, such in the case of NSCLC, is one of the challenges of dose accuracy. The target movement during radiation treatment causes dose blurring and interplay effects. A previous study proved that internal margins on PTV reduce the differences between plan and measured doses. This study aims to observe the effect of robust optimization, which provide uncertainty of target volume position on photon planning. We compared the robust with a conventional method on the in-house thorax dynamic phantom. This method enhanced the dose conformity index in the IMRT and VMAT techniques and the dose uniformity in the VMAT technique. However, robust planning reduces the steepness of the dose in both IMRT and VMAT. The average target dose of IMRT technique was increased from 199.63 cGy in conventional planning to 200.43; 206.26; and 204.20 cGy for planning with an uncertainty of 5 mm, 10 mm and 15 mm. On the other hand, the average target dose was reduced from 201.59 cGy in conventional planning to 198.84; 199.05; and 199.06 cGy with an uncertainty of 5 mm, 10 mm and 15 mm for VMAT techniques, respectively. We found that the robust plan delivered a higher dose at OAR near the target than the conventional plan, but the dose is lower in the other areas on the IMRT technique. For VMAT, most of the OAR achieved a higher dose on a robust photon plan.

Abstrak :
This paper addresses a new robust multi objective multi period model for supply chain planning under uncertainty considering quantity discounts. The proposed model maximizes the current proht of the distributor by making a balance between the total costs of the supply chain and the distributor company s revenues of selling products and also maximizes the company s expected profit by introducing brands and taking the risk of loss on it. Considering uncertainty in the purchasing cost, selling fees, and demand fluctuations, the new robust multi objective mixed integer programming model is solved as a single objective mixed integer programming model by utilizing the LP metrics method. By settling regulatory penalty parameters and considering different economic scenarios, the robustness and effectiveness of the developed model are verified with the data from BEH PAKHSH Company, a commodities distributor in Iran. The outcomes show that the proposed model is a promising approach to run an efficient supply chain.

Abstrak :
Plastik merupakan bahan yang sering dipakai karena plastik memiliki ketahanan yang baik, mudah digunakan dan harganya yang murah. Hal ini membuat plastik banyak dibutuhkan oleh berbagai industri, sehingga jumlah produksi plastik di Indonesia meningkat setiap tahunnya. Peningkatan pada produksi plastik membuat jumlah timbulan sampah plastik yang dihasilkan pun meningkat. Sampah plastik yang tidak terkelola dengan baik dapat berdampak buruk terhadap lingkungan dan manusia. Salah satu cara untuk mengurangi dampak negatif dari peningkatan jumlah sampah plastik ini adalah mendesain jaringan reverse logisticsnya. Kondisi ketidakpastian terjadi dalam reverse logistics di Indonesia dimana data terbatas ketersediaannya serta berfluktuasi dari waktu ke waktu. Pada penelitian ini, diusulkan model Optimisasi Robust untuk desain jaringan reverse logistics sampah plastik di Indonesia. Optimisasi Robust digunakan untuk menangani ketidakpastian data yang terjadi pada parameter jumlah sampah yang dikembalikan konsumen. Penyelesaian model secara numerik pada Python juga dilakukan menggunakan data reverse logistics sampah plastik di DKI Jakarta. Dengan mempertimbangkan aspek ekonomi, sosial dan lingkungan, didapat hasil dari penyelesaian model tersebut berupa lokasi dan alokasi sampah plastik yang optimal. ......Plastic is a wear resistance, easy to use, and cheap material. It was required by so many industries, so the quantity of plastic production in Indonesia increases every year. The increase in plastic production makes the volume of plastic waste generated by households. The unmanaged plastics waste releases various harmful substances for humans and the environment. To reduce this negative impact, a reverse logistics network for plastic waste, the recovery flows of plastic waste, is designed. Conditions of uncertainty occur in the reverse logistics of Indonesian plastic waste where the data is still limited in the availability and the data fluctuates over time. This study proposed a Robust Optimization model for reverse logistics network design of plastic waste management in Indonesia. Robust Optimization is used to handle the data uncertainty of the quantity of returned plastic from the consumer. Reverse logistics data of plastic waste in DKI Jakarta is also used to do numerical model calculation in Python. The optimal location of selected facilities and the quantity of plastic transported from one facility to the others are obtained, with social, economic, and environmental considerations

Abstrak :
This book discusses the recent developments in robust optimization (RO) and information gap design theory (IGDT) methods and their application for the optimal planning and operation of electric energy systems. Chapters cover both theoretical background and applications to address common uncertainty factors such as load variation, power market price, and power generation of renewable energy sources. Case studies with real-world applications are included to help undergraduate and graduate students, researchers and engineers solve robust power and energy optimization problems and provide effective and promising solutions for the robust planning and operation of electric energy systems.