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International Journal of Industrial Optimization (IJIO)
Published by Universitas Ahmad Dahlan
ISSN : 27146006     EISSN : 27233022     DOI : https://doi.org/10.12928/ijio.v1i1.764
Core Subject : Science, Engineering,
Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering
The Journal invites original articles and not simultaneously submitted to another journal or conference. The whole spectrums of Industrial Engineering are welcome but are not limited to Metaheuristics, Simulation, Design of Experiment, Data Mining, and Production System. 1. Metaheuristics: Artificial Intelligence, Genetic Algorithm, Particle Swarm Optimization, etc. 2. Simulations: Markov Chains, Queueing Theory, Discrete Event Simulation, Simulation Optimization, etc. 3. Design of experiment: Taguchi Methods, Six Sigma, etc. 4. Data Mining: Clustering, Classification, etc. 5. Production Systems: Plant Layout, Production Planning, and Inventory Control, Scheduling, System Modelling, Just in Time, etc.
Arjuna Subject : Teknik (semua kategori) - Tenik Industri dan Manufaktur
Articles 94 Documents
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Using machine learning to predict the number of alternative solutions to a minimum cardinality set covering problem Emerick, Brooks; Lu, Yun; Vasko, Francis J.
International Journal of Industrial Optimization Vol 2, No 1 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i1.2948

Abstract

Although the characterization of alternative optimal solutions for linear programming problems is well known, such characterizations for combinatorial optimization problems are essentially non-existent. This is the first article to qualitatively predict the number of alternative optima for a classic NP-hard combinatorial optimization problem, namely, the minimum cardinality (also called unicost) set covering problem (MCSCP). For the MCSCP, a set must be covered by a minimum number of subsets selected from a specified collection of subsets of the given set. The MCSCP has numerous industrial applications that require that a secondary objective is optimized once the size of a minimum cover has been determined. To optimize the secondary objective, the number of MCSCP solutions is optimized. In this article, for the first time, a machine learning methodology is presented to generate categorical regression trees to predict, qualitatively (extra-small, small, medium, large, or extra-large), the number of solutions to an MCSCP. Within the machine learning toolbox of MATLAB®, 600,000 unique random MCSCPs were generated and used to construct regression trees. The prediction quality of these regression trees was tested on 5000 different MCSCPs. For the 5-output model, the average accuracy of being at most one off from the predicted category was 94.2%. 
Optimizing the clinker production by using an automation model in raw material feed Sutawijaya, Ahmad Hidayat; Kayi, Abdul
International Journal of Industrial Optimization Vol 2, No 1 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i1.3002

Abstract

The clinker production process involves much equipment and material flow; thus, an operating system is needed to regulate and manage the production process. XYZ company uses an operating system for clinker production called Cement Management Quality (CMQ). The CMQ operation on clinker production is considered semi-automatic because it requires many interventions from the operator. Furthermore, the program is limited under specific condition. As a result, the quality of the clinker is decreased, and the energy consumption is increased. The failure of clinker production is related to the CMQ system, and it is vital to solving the problem appropriately. Since the CMQ system is connected with many aspects, it is essential to find the root cause. Root Cause Analysis (RCA) method is suitable to find the root of the problem for a complex system. After researching using RCA, the main problems on the CMQ system is the data not appropriately integrated, and the process algorithm is insufficient. The new integration of data transfer and new algorithms are developed as an attempt to solve the issues. The new data integration model and algorithm are applied through the simulation method as a test case before taking complete corrective action on the CMQ system. The new model's application shows the standard deviation of the process is decreased under the specified threshold. The method provides good results for improving the quality of the clinker production process. It can be used as an essential reference for applying the automation model in the clinker production process.
A Dai-Liao Hybrid Hestenes-Stiefel and Fletcher-Revees Methods for Unconstrained Optimization Salihu, Nasiru; Odekunle, Mathew Remilekun; Saleh, Also Mohammed; Salihu, Suraj
International Journal of Industrial Optimization Vol 2, No 1 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i1.3054

Abstract

Some problems have no analytical solution or too difficult to solve by scientists, engineers, and mathematicians, so the development of numerical methods to obtain approximate solutions became necessary. Gradient methods are more efficient when the function to be minimized continuously in its first derivative. Therefore, this article presents a new hybrid Conjugate Gradient (CG) method to solve unconstrained optimization problems. The method requires the first-order derivatives but overcomes the steepest descent method’s shortcoming of slow convergence and needs not to save or compute the second-order derivatives needed by the Newton method. The CG update parameter is suggested from the Dai-Liao conjugacy condition as a convex combination of Hestenes-Stiefel and Fletcher-Revees algorithms by employing an optimal modulating choice parameterto avoid matrix storage. Numerical computation adopts an inexact line search to obtain the step-size that generates a decent property, showing that the algorithm is robust and efficient. The scheme converges globally under Wolfe line search, and it’s like is suitable in compressive sensing problems and M-tensor systems.
Designing project schedule using crashing method to compress the fiber to the home project schedule Anugerah, Zha Sha Putri; Pratami, Devi; Akbar, Mohammad Deni
International Journal of Industrial Optimization Vol 2, No 1 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i1.3025

Abstract

ABC Company is an agent of network construction, operation, and maintenance. ABC Company is currently implementing the STTF (Shit to the Front) project, which is the project to add FTTH (Fiber to the Home) networks in areas that can have high customer demand. One of the STTF project construction sites is the Indra Prahasta II housing location. However, the project is currently experiencing work delays due to the Covid-19 disaster in Indonesia. Delays in project execution can result in potential prospects choosing another company that provides similar services. The project schedule can be accelerated using the crashing method and TCTO (Time Cost Trade-Off) analysis to solve this problem. This research's acceleration will be carried out with alternatives for adding 3 hours, 2 hours, 1 hour, and an alternative to increasing workers' number. This project has an average duration of 55 working days with a total cost of Rp 604,124,460. The results obtained from data processing, on the alternative of adding 1 hour of overtime work, the total duration becomes 54 working days with total project cost is Rp 605,734,138. In addition to 2 hours of overtime work, the project's total duration can be reduced to 54 days with a total project cost Rp 606,803,619. And for the addition of 3 hours overtime, the total duration can be shortened to 54 days with a total cost of Rp 606,803,619. As for increasing the number of workers, project work duration can be shortened to 54 working days with a total project cost Rp 604,556,748
Implementation of lean thinking through A3 report in plastic injection company Rini, Sartika
International Journal of Industrial Optimization Vol 2, No 1 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i1.3055

Abstract

Lean thinking, or lean production, which has long been introduced by Toyota, is a process improvement concept that is carried out by eliminating waste and focusing more on things that create values. Its emergence was inspired by the fact on the production floor, where only a small fraction of the total times and efforts contributed to creating added value to customers’ final product. Lots of prior studies have shown various benefits of implementing lean production, especially in manufacturing industries. However, many companies still find difficulties trying to implement a lean approach for the first time. Furthermore, they do not have a clear and concise picture of each component of the lean approach they want to apply. This company is based on case study which has many rejected products so that it makes higher production cost. Therefore, this study proposed an implementation of lean thinking to reduce the number of rejected products through A3 report. This result show the defects can be reduced and the standard operational procedure has been developed. 
Integration of lot sizing and scheduling models to minimize production cost and time in the automotive industry Badri, Huda Muhamad; Khamis, Nor Kamaliana; Ghazali, Mariyam Jameelah
International Journal of Industrial Optimization Vol 1, No 1 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v1i1.2753

Abstract

Lot planning and production scheduling are important processes in the manufacturing industry. This study is based on the case study of automotive spare parts manufacturing firm (Firm-A), which produces various products based on customer demand. Several complex problems have been identified due to different production process flows for different products with different machine capability considerations at each stage of the production process. Based on these problems, this study proposes three integrated models that include lot planning and scheduling to minimize production costs, production times, and production costs and time simultaneously. These can be achieved by optimizing model solutions such as job order decisions and production quantities on the production process. Next, the genetic algorithm (GA) and the Taguchi approach are used to optimize the models by finding the optimal model solution for each objective. Model testing is presented using numerical examples and actual case data from Firm-A. The model testing analysis is performed using Microsoft Excel software to develop a model based on mathematical programming to formulate all three objective functions. Meanwhile, GeneHunter software is used to represent the optimization process using GA. The results show production quantity and job sequence play an essential role in reducing the cost and time of production by Rp 42.717.200,00 and 31392.82 minutes (65.4 days), respectively. The findings of the study contribute to the production management of Firm-A in helping to make decisions to reduce the time and costs of production strategically, where it provides a guideline for complex production activities.
Sentiment analysis on myindihome user reviews using support vector machine and naïve bayes classifier method Hakim, Sulton Nur; Putra, Andika Julianto; Khasanah, Annisa Uswatun
International Journal of Industrial Optimization Vol 2, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i2.4437

Abstract

In the era of globalization, the internet has become a human need in doing various things. Many internet users are an opportunity for internet service providers, PT Telekomunikasi Indonesia (Telkom). One of PT Telkom's products is IndiHome. As the only state-owned enterprise engaged in telecommunications, PT Telkom is expected to meet the needs of the Indonesian people. However, based on the rating obtained by IndiHome products through the myIndiHome application on Google Play, it is 3.5 out of 87,000 more reviews. The reviews focus on how important the effect of word-of-mouth is on choosing and using internet provider products. The review data was collected on November 1, 2020 to December 15, 2020, with a total of 2,539 reviews as a sample.  The sentiment analysis process that has been carried out shows that the number of reviews included in the negative sentiment class was 1.160 reviews, and the positive class was 1.374 reviews out of a total of 2,539 reviews. The results indicate that service errors in IndiHome services are still quite high, reaching 46.7% as indicated by the number of negative reviews. The classification results show that the average value of the total accuracy of the Support Vector Machine (SVM) method is 86.54% greater than Naïve Bayes Classifier (NBC) method which has an average total accuracy of 84.69%.  Based on fishbone diagram analysis, there are 12nd problems on negative reviews that classify problems 5P factors: Price, People, Process, Place, and Product.
Marketing strategy planning at alfamart lodadi stores using the clustering, ahp, and ar-mba method Azhra, Fariza Halidatsani; Fadhlurrohman, Najib; Putra, Bagas Swardhana; Ibrahim, Faisal
International Journal of Industrial Optimization Vol 2, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i2.4361

Abstract

Nowadays, people are very facilitated by the existence of various shopping centers, including retail. Because many retailers are close to each other, Alfamart Lodadi must have a good marketing strategy. So far, the strategy used is sometimes inaccurate because it is not based on customer segmentation.  Therefore, the purpose of this research is to help retail owners to make decisions regarding the right marketing strategy with three methods so that Alfamart Lodadi can compete and increase sales. The Analytical Hierarchy Process (AHP) is employed to find the priority variables of customer segmentation; meanwhile, the K-Means Clustering is used to group customers based on the similarity of predetermined characteristics. AR-MBA is used to find out the best rules, and products are rarely, sufficient, and frequently purchased.  The results of this research, based on AHP, obtained five segmentation priority variables based on the largest eigenvector values. There are income, age, expenditure, distance, and shopping intensity with each eigenvector value of 0.13; 0.16; 0.12; 0.12; 0.17. From clustering, there are three customer clusters with different strategies, including free shipping when shopping, product discounts for certain periods, and providing catalogs and discounts on each transaction and offer notifications. Then, this research also obtained three strategies based on AR-MBA. These include making a catalog by bringing frequently purchased products closer together, choosing a layout for shopping places by bringing frequently purchased products closer together, and making shopping coupons for rarely purchased products. With several strategic choices, companies can make decisions appropriately according to the desired criteria.
Multi-item inventory policy with time-dependent pricing and rework cost Nafisah, Laila; Maharani, Nabilla Clara Devi; Astanti, Yuli Dwi; Khannan, Muhammad Shodiq Abdul
International Journal of Industrial Optimization Vol 2, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i2.4370

Abstract

The price of broiler chickens at the consumer level varies daily. The price can be very low or otherwise. The price has resulted from the imbalance between the availability of chicken from suppliers and the market demand. As a result, demand will also fluctuate because it is influenced by consumer purchasing power. When the price of live chickens is low, the carcass company will usually buy in large quantities and expect to sell them at a higher price. The problem arises when the chicken overstock company will risk product damage due to product buildup in the refrigerated warehouse, so rework is necessary. In this paper, we will be developed a multi-item inventory model that considers material prices that vary to time, probabilistic demand, and rework costs. The aim is to determine the right policy for controlling frozen chicken products' inventory to minimize losses and total inventory costs.  This model can evaluate the best time to order broiler chickens, how much to order, how long the interval between orders, and the optimal number of orders, resulting in minimum total inventory cost per period.  The model solution is carried out with an optimization approach based on the parameters that affect the model. A numerical example is given at the end of this paper for model validation and illustrates the model solving algorithm.
Ceramic supplier selection using analytical hierarchy process method Rahmiati, Filda; Syafei, H.M Yani; Purwanto, Purwanto; Andianto, Jonathan
International Journal of Industrial Optimization Vol 2, No 2 (2021)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/ijio.v2i2.4406

Abstract

This study tried to implement the Analytical Hierarchy Process (AHP) and the weights of the criteria and sub-criteria to find the best supplier. According to QCDFR (quality, cost, delivery, flexibility, and responsiveness). This study took place in one of the biggest tile producers, ranks fifth in the world and the first in Indonesia. However, the company currently only uses quality, cost, and delivery methods to choose the best supplier of raw material, namely feldspar. This research tries to use the systematic method to find the best supplier based on the importance of the criteria. The method used the quantitative approach to enumerate the data to analyze the information.  The company analyzed six suppliers. The primary tool used in this research is a Super Decision Software version 3.2 to create and manage the AHP model, enter the judgments, get results, and perform sensitivity analysis on the results. The result found that Semarang is the best supplier. The company will choose Semarang to become the company's business partner compared to the other suppliers because Semarang has met the criteria that the company prioritizes the most. By having the best supplier selection, the company can provide the right material consistency and suitable material suitability.

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