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"ABSTRACTThis study considers the real situations of production between the products and the setup of production tools that are different. Therefore, this study considers the setup time of work stations and production batch in the production scheduling. This study proposed a random optimization algorithm with multi objective that can be selected to optimize the scheduling performance. VIP customers priorities, urgent orders, and asymmetrical setup times are considered. The objectives of this study include minimum makespan, minimum total delayed penalty, and minimum total number of delayed orders. After cases testing, we found that the proposed algorithm can improve the production performance efficiently."

"Most classical scheduling approaches deal with single products, single machines, and static manufacturing environments. In real-world manufacturing systems, however, scheduling can be assigned for multi-item production on multimachines in a dynamic environment in which unexpected new orders may be received. This paper focuses on scheduling problems in an assembly job shop with parallel machines that produce multi-item multi-level products. Models were developed for due date fulfillment and due date assignment in static and dynamic conditions, with the objectives of minimizing total actual flow time, while considering the defect rate at each stage of the process. The insertion technique was used in the scheduling process; insertion can be performed in batch operations at all available positions on all machines. A hypothetical case of job shop scheduling problems associated with multi-item, multi-level production on parallel machines was studied, and the computational results demonstrated the validity of the proposed algorithms."

"ABSTRAKKetersediaan gas bumi sebagai bahan baku untuk produksi urea terus menurun dan harganya semakin meningkat, hal ini mendorong pengembangan produksi gas sintesis yang ekonomis dan aman dari aspek lingkungan untuk diterapkan dalam industri green urea dari proses steam reforming, gasifikasi biomassa, PV Elektrolisis, dan kombinasi dari ketiga proses tersebut. Metode Analytical Hierarchy Process AHP digunakan untuk proses seleksi teknologi dan pendekatan Multi-Objective Optimization MOO digunakan untuk meminimalkan biaya produksi dan dampak lingkungan dari produksi urea untuk setiap teknologi dengan memperhitungkan learning curve dari belanja modal Capex , harga bahan baku untuk setiap teknologi dan nilai uang di masa depan hingga tahun 2050. Model mencakup dua fungsi obyektif yang dihitung untuk mencari biaya produksi green urea dan emisi CO2 terendah. Hasilnya menunjukkan bahwa teknologi gasifikasi biomassa dari tahun 2020 hingga 2040 dan teknologi kombinasi gasifikasi biomassa-PV Elektrolisis tanpa baterai dari tahun 2040 hingga 2050 yang paling memenuhi biaya produksi dan emisi CO2 minimum.

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ABSTRACTThe availability of natural gas as a feedstock for urea production continues to decline and its price increases, it encourages synthesis gas production development that is easy to implement, economical and relatively safe for the environment to be applied in green urea industry from steam reforming, biomass gasification, PV Electrolysis, and a combination of these three processes. The Analytical Hierarchy Process AHP method for technology selection process and The Multi Objective Optimization MOO approach is used to minimize the production costs and environmental impacts of green urea production for each technology considering the learning curve of capital expenditure Capex and feedstock price for each technology and future value until 2050. The model includes two competing objective functions to seek the lowest cost of green urea production and the lowest CO2 emissions.The result suggests that biomass gasification technology from 2020 to 2040 and combine biomass gasification PV Electrolysis without battery technology from 2040 to 2050 fulfill the minimum production cost and minimum CO2 emissions."

"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."

"This paper provides a developed mathematical model to derive the optimal integrated lot sizing in a multi-level supply chain with imperfect quality products. The developed mathematical model has a bi-objective function, with conflicting goals, minimizing the chain inventory costs and maximizing the chain total profit aided to find optimum policy for integrated lot sizing. We further actualize the problem by assuming multiple stochastic constraints. The mathematical formulation of the problem is stochastic, nonlinear, and large. In this regard, the interior point algorithm that is developed as more effective algorithm with less iteration is used for solving the recent convex nonlinear model. Numerical example shows that the developed interior point method is an efficient method with excellent performance in terms of the quality of the solution. Also, Sensitivity analysis shows that the developed interior point method is an efficient method with excellent performance in terms of the quality of the solution."

"Setup dalam proses produksi adalah hal yang sifatnya harus, banyak point penting yang harus dilakukan dalam proses setup, karena proses produksi yang baik dan hasil produksi yang baik sangat ditentukan oleh proses setup yang baik dan benar. Akan tetapi ada efek negatif dari setup, yaitu timbulnya kerugian baik dari segi waktu maupun dari segi scrap produk. Hal tersebut dikarenakan waktu setup yang lama. Demikian juga dalam proses produksi magnet wire, proses setup termasuk salah satu penyumbang kerugian. Penelitian ini akan meneliti bagaimana cara menurunkan waktu setup sehingga kerugian akibat setup bisa diminimalkan. Metode yang digunakan adalah Single Minute Exchange of Die dan hasilnya adalah berkurangnya waktu setup dan berkurangnya scrap karena waktu setup yang berkurang.

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Setup in the production process is of its nature must be, many important points that must be done in the setup process, because the production process and production results largely determined by the setup process. However, there are negative effects of the setup, namely the emergence of losses both in terms of time and in terms of product scrap. That is because a long setup time. Likewise in the magnet wire production process, the setup process is one contributor to losses. This research will examine how to reduce setup times so that losses can be minimized due to the setup, method used is Single Minute Exchange of dies , there are two outcomes of reduced setup time and scrap because of the setup process time is also reduced."

"ABSTRAKBreakwater adalah bangunan penahan gelombang yang memiliki karakteristik pekerjaan yang bersifat repetitif dalam volume yang besar. Karakteristik dari proyek ini menuntut perencana untuk membuat suatu metode perencanaan penjadwalan yang berbeda dari bentuk metode biasa seperti CPM dan bar chart, dimana metode ini tidak cocok untuk penjadwalan pekerjaan yang repetitif. Metode penjadwalan yang cocok untuk digunakan dalam pembangunan proyek yang bersifat repetitif ialah metode penjadwalan linier. Penelitian ini bertujuan untuk mengaplikasikan metode penjadwalan linier dengan pendekatan multi-objective genetic optimization menggunakan software Evolver pada pembangunan breakwater di Pelabuhan Kalibaru. Pengoptimalisasian ditinjau dari segi jumlah tim pekerja dan total interupsi pekerjaan yang akan meminimalisasikan total durasi dan biaya proyek. Setelah dilakukan pengaplikasian dengan menggunakan metode ini, terjadi penurunan durasi sebesar 31,79% dan penurunan biaya sebesar 3,04%. Metode ini dapat digunakan dalam pengaplikasian dan pengoptimalisasian pembangunan breakwater di Pelabuhan Kalibaru.

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ABSTRACTBreakwater is a wave barrier building which has the characteristic of repetitive work in large volume of activities. Characteristics of this project requires planners to make a method of scheduling that is different from the usual form of scheduling method such as CPM and bar chart, where this method is not suitable for scheduling repetitive work. The scheduling method that suitable for repetitive construction project is linear scheduling method.This study aims to apply the linear scheduling method with multi-objective genetic optimization approach using Evolver software in breakwater Kalibaru Port construction. Optimizing in terms number of crew and total work interuption that will minimize total project duration and cost. After the application of this method, there is a decrease in duration of 31,79% and an impairment charge of 3,04%. This method can be used in application and optimization breakwater Kalibaru Port construction."

"ABSTRAKDisertasi ini membahas penerapan metode estimasi Continuum GMM pada model struktural pergerakan imbal hasil saham pada selang-selang waktu acak, yang dikenal dengan model DMHT. Model ini mendefenisikan durasi antar perdagangan sebagai waktu yang dibutuhkan oleh gerak Brown standar dengan drift, menventuh daerah acak tertentu, sedangkan nilai-nilai imbal hasil yang terjadi, dimodelkan oleh gerak Brown tambahan, yang terkorelasi. Penaksir CGMM untuk parameter-parameter model DMHT selanjutnya dikonstruksi sebagai jarak minimal antara momen-momen teoretis dan momen-momen empiris, dengan mempertimbangkan semua kemungkin- an momen yang dapat dibentuk dari fungsi karakteristik gabungan bersvarat da ri durasi antar transaksi dan imbal hasil, dengan rumusan jarak tertentu.Teknik estimasi yang diusulkan ini memfasilitasi penghitungan dan penanganan problem- problem yang terkait dengan kekeliruan diskritisasi dalam kondisi-kondisi momen dan tidak tersedianva fungsi densitas gabungan bersvarat dari model. Aplikasi em piris dengan menggunakan data level transaksi dari dua saham dengan kapitalisasi pasar yang berbeda, yang diperdagangkan di Bursa Efek Indonesia BEI dilakukan. Hasilnva mengindikasikan bahwa hubungan antara durasi dan volatilitas imbal hasil sangat persisten dan ada hubungan instan negatif antara volatilitas dan durasi kon- temporer. Implikasi dari kausalitas instan antara volatilitas dan durasi kontemporer juga diteliti. Studi Monte Carlo memperlihatkan bahwa penaksir CGGM mendo- minasi performa statistik dibandingkan penaksir GMM dengan jumlah momen yang terbatas, dan pelibatan endogenitas dari durasi antar transaksi akan memperbaiki akurasi statistik dari ukuran variansi imbal hasil.

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ABSTRACTThis dissertation studies the implementation of Continuum-GMM CGMM esti mation method to the structural model of stock returns movements in the random time intervals. The model which is known as the dynamic mixed hitting time mo del DMHT defines duration between trades as the waiting time of one component of a bivariate standard Brownian motion to hit a given random boundary. Mea nwhile, another correlated Brownian motion generates the marks such as market price and trading volume. In this research, the CGMM estimator of the DMHT mo del is the minimum distance between theoretical moments defined from the model and empirical moments defined from the data , by considering all possible momen ts constructed from the conditional joint characteristic function of durations and returns.The proposed estimation technique facilitates computation and overcomes problems related to the discretization error and to the non-tractable conditional joint probability density function. Empirical applications using transaction level da ta from two shares traded in Indonesia stock exchange ISX , with different market capitalization, are conducted. The result of empirical applications indicate that cor relation between durations and return volatility is highly persistent, and there are a negative instantaneous causality between volatility and contemporaneous duration. The implication of instantaneous causality between volatility and contemporaneous duration is also studied. The result of Monte Carlo studies showed that CGMM estimator dominates the other traditional GMM estimators with a few number of moments, in terms of their statistical performance. Monte Carlo studies also show that the involvement of endogeneity of the duration between transaction will improve our statistical accuracy of return variance estimators."

"Indonesia memiliki potensi biomassa yang sangat besar, salah satunya adalah Tandan Kosong Kelapa Sawit (TKKS) yang mengandung lignoselulosa. Penelitian ini bertujuan untuk mengoptimumkan proses konversi TKKS menjadi etanol, furfural, dan listrik melalui prinsip ko-produksi supaya menghasilkan performa ekonomi dan lingkungan yang optimum. Performa ekonomi diukur dengan NPV, sedangkan performa lingkungan diukur melalui emisi CO2 hasil analisis life cycle. Hasil simulasi proses pada Unisim dan SuperPro kemudian diregresi menggunakan MATLAB ke dalam persamaan-persamaan polinomial yang selanjutnya dioptimisasi oleh GAMS. Optimisasi multi-objektif secara simultan mampu menunjukkan kapasitas dan kondisi operasi optimum yang dihasilkan dalam bentuk kurva Pareto. Daerah optimum didominasi oleh temperatur hidrolisis terendah, yaitu 162 oC di mana biaya produksi etanol sebesar 1,02 $/liter pada solusi NPV maksimum dan faktor emisi 21,698 kg-CO2/kg-furfural; 2,818 kg-CO2/MJ-etanol; serta 3,180 kg-CO2/MJ-listrik pada solusi emisi CO2 minimum.

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Indonesia has huge potential in Palm Oil Empty Fruit Bunch (EFB) which is a lignocellulosic biomass. The purpose of this research is to optimize the conversion process of EFB to ethanol, furfural, and electricity through co-production, to achieve optimum economic and environmental performances. Economic performance is measured by NPV, while environmental performance by CO2 emission through life cycle analysis.

The process simulation results from Unisim and SuperPro are regressed using MATLAB into polynomial equations which are optimized using GAMS. The multi-objective optimization simultaneously determines optimum capacity and operating condition, which are represented by Pareto curve. The optimum solutions are dominated by the lowest hydrolysis temperature 162 oC, and reveal production cost of ethanol, which is $1,02/litre for the maximum NPV solution, and emission factor 21,698 kg-CO2/kg-furfural; 2,818 kg-CO2/MJ-ethanol; and 3,180 kg-CO2/MJ-electricity for the minimum emission solution."

"Penelitian ini bertujuan untuk mengoptimumkan konversi TKKS menjadi etanol, furfural, dan listrik yang terintegrasi dengan sistem generasi kukus agar menghasilkan performa ekonomi dan lingkungan yang optimum. Performa ekonomi diukur dengan NPV (net present value) sedangkan performa lingkungan diukur melalui emisi CO2 hasil analisis life cycle. Hasil optimisasi menunjukkan bahwa suhu optimum untuk reaksi hidrolisis adalah 180°C dan pemenuhan fraksi kukus massa dari generasi kukus tenaga surya yang optimum berada pada rentang 0-0,28 yang ditunjukkan oleh kurva Pareto. CSP mampu memenuhi seluruh kebutuhan kukus secara finansial pada pembangunan unit ke-10 dengan proyeksi learning curve. Split fraksi TKKS untuk objektif optimum didapatkan pada fraksi massa TKKS sebesar 0.25 ke unit reaktor hidrolisis.

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The purpose of this research is to optimize the conversion process of EFB to ethanol, furfural, and electricity through co-production principal integrated with solar-assisted steam generation system, to achieve optimum economic and environmental performances. Economic performance is measured by NPV, while environmental performance by CO2 emission through life cycle analysis. The multi-objective optimization shows that the optimum temperature of hydrolisis reaction is 180°C and solar-assisted generation system is applicable for fulfilling steam need until 0,28 of mass fraction, which are represented by Pareto curve. CSP can fulfill all demand of steam funancially when the 10th unit established by learning curve projection. Fraction split of EFB into hydrolisis reactor is optimum at 0,25."