Showing papers in "International Journal of Industrial Optimization (IJIO) in 2022"
TL;DR: The primary contribution of this article is that it demonstrates, customized to each category, how general-purpose integer programming software (CPLEX in this case) can be iteratively used to efficiently generate bounded solutions for MDMKPs.
Abstract: A generalization of the 0-1 knapsack problem that is hard-to-solve both theoretically (NP-hard) and in practice is the multi-demand multidimensional knapsack problem (MDMKP). Solving an MDMKP can be difficult because of its conflicting knapsack and demand constraints. Approximate solution approaches provide no guarantees on solution quality. Recently, with the use of classification trees, MDMKPs were partitioned into three general categories based on their expected performance using the integer programming option of the CPLEX® software package on a standard PC: Category A—relatively easy to solve, Category B—somewhat difficult to solve, and Category C—difficult to solve. However, no solution methods were associated with these categories. The primary contribution of this article is that it demonstrates, customized to each category, how general-purpose integer programming software (CPLEX in this case) can be iteratively used to efficiently generate bounded solutions for MDMKPs. Specifically, the simple sequential increasing tolerance (SSIT) methodology will iteratively use CPLEX with loosening tolerances to efficiently generate these bounded solutions. The real strength of this approach is that the SSIT methodology is customized based on the particular category (A, B, or C) of the MDMKP instance being solved. This methodology is easy for practitioners to use because it requires no time-consuming effort of coding problem specific-algorithms. Statistical analyses will compare the SSIT results to a single-pass execution of CPLEX in terms of execution time and solution quality.
2 citations
TL;DR: In this article , the authors focused on selecting the best alternative location by considering seven criteria: geography, cost, population, risk, facilities & infrastructure, availability of human resources, and developer credibility.
Abstract:
CHUUO Plain Shirt Factory is a plain shirt manufacturer founded in 2016 and is located at Kaliurang road Km 9, Yogyakarta. They not only sell plain t-shirts but also sell screen printing shirts, receive screen printing services, and orders to make collared shirts (polo). For CHUUO Plain Shirt Factory, business location has an important role in the marketing process related to reaching the customers. One method that can be used to determine the location of a new business is Analytical Hierarchy Process (AHP). This study focuses on selecting the best alternative location by considering seven criteria: geography, cost, population, risk, facilities & infrastructure, availability of human resources, and developer credibility. The research method used was observation and direct interviews using a questionnaire. The result shows that alternative location A (Shop at Gejayan Road No.30) has the highest all weight evaluation value (0.45). Alternative location B (Shop at Kaliurang Road Km 4) has a value of all weight evaluation of 0.3. Alternative location C (Shop at Magelang Road Km 7) has valued all weight evaluations the lowest (0.25). Based on the analytical research conducted, it can be concluded that alternative location A (Shop at Gejayan Road No.30) is the best location to open a branch shop for CHUUO Plain Shirt Factory.
1 citations
TL;DR: The proposed metaheuristic, called HEDAMMF (Hybrid Estimation of Distribution Algorithm with Mallows model and Moth-Flame algorithm), improves the performance of recent algorithms and has a better performance, or equal in effectiveness, than recent algorithms.
Abstract: This paper considers solving more than one combinatorial problem considered some of the most difficult to solve in the combinatorial optimization field, such as the job shop scheduling problem (JSSP), the vehicle routing problem with time windows (VRPTW), and the quay crane scheduling problem (QCSP). A hybrid metaheuristic algorithm that integrates the Mallows model and the Moth-flame algorithm solves these problems. Through an exponential function, the Mallows model emulates the solution space distribution for the problems; meanwhile, the Moth-flame algorithm is in charge of determining how to produce the offspring by a geometric function that helps identify the new solutions. The proposed metaheuristic, called HEDAMMF (Hybrid Estimation of Distribution Algorithm with Mallows model and Moth-Flame algorithm), improves the performance of recent algorithms. Although knowing the algebra of permutations is required to understand the proposed metaheuristic, utilizing the HEDAMMF is justified because certain problems are fixed differently under different circumstances. These problems do not share the same objective function (fitness) and/or the same constraints. Therefore, it is not possible to use a single model problem. The aforementioned approach is able to outperform recent algorithms under different metrics for these three combinatorial problems. Finally, it is possible to conclude that the hybrid metaheuristics have a better performance, or equal in effectiveness than recent algorithms.
1 citations
TL;DR: In this paper , a convolutional neural network model called GraphoNet is built and optimized using Particle Swarm Optimization (PSO) to optimize epoch, minibatch, and droupout parameters.
Abstract: Graphology or handwriting analysis can be used to infer the traits of the writers by examining each stroke, space, pressure, and pattern of the handwriting. In this study, we infer a six-dimensional model of human personality (HEXACO) using a Convolutional Neural Network supported by Particle Swarm Optimization. These personalities include Honesty-Humility, Emotionality, eXtraversion, Agreeableness (versus Anger), Conscientiousness, and Openness to Experience. A digital handwriting sample data of 293 different individuals associated with 36 types of personalities were collected and derived from the HEXACO space. A convolutional neural network model called GraphoNet is built and optimized using Particle Swarm Optimization (PSO). The PSO is used to optimize epoch, minibatch, and droupout parameters on the GraphoNet. Although predicting 32 personalities is quite challenging, the GraphoNet predicts personalities with 71.88% accuracy using epoch 100, minibatch 30 and dropout 52% while standard AlexNet only achieves 25%. Moreover, GraphoNet can work with lower resolution (32 x 32 pixels) compared to standard AlexNet (227 x 227 pixels).
1 citations
TL;DR: In this paper , the authors used the DFMA method to analyze and design a water filter for Kembang Belor Village in South Korea, which reduced production costs and increased the efficiency of design and assembly time.
Abstract: Kembang Belor Village is one of the villages that have a water resource but are not yet precisely utilized and need a water filter. The current water filter is not suited for users’ needs because they cannot afford it. Therefore, this research intends to redesign the water filter. This research aims to reduce production costs and increase the efficiency of design and assembly time. The method employed is Design for Manufacturing and Assembly (DFMA). The results show that the production cost decreased by 50.83%; design efficiency increased by 37.5%; production, handling, and assembly time improved by 51.7%, 33.3%, and 52.7% for each; the number of ppm decreased from 142 to 95. For the contribution, few previous research uses the DFMA method to analyze and redesign the water filter. These findings contribute in helping the user recognize new options to design efficient water filters for future needs.
TL;DR: In this paper , a cyclone performance inlet scroll type separator with helical angle was investigated, experimental and development methods to get optimal performance where pressure drop and efficiency are indications of cyclone separator performance, the use of Taguchi experimental design produces different factors and levels so that multi-response methods such as PCR and TOPSIS was used to produce the best combination of factors this paper .
Abstract: Pollutant control uses cyclone separators as pre-cleaners and is widely used in manufacturing and mining industries. Research on cyclone performance is carried out with changes in various variations that affect it, the problem that occurs is that multi-response can give results of different factors and levels as a result of equipment design cannot provide optimal results and research topics on inlet scroll types have not been widely carried out, this study aims to improve cyclone performance inlet scroll type separator with helical angle, experimental and development methods to get optimal performance where pressure drop and efficiency are indications of cyclone separator performance, to get optimal performance the use of Taguchi experimental design produces different factors and levels so that multi-response methods such as PCR and TOPSIS was used to produce the best combination of factors and levels, confirmation experiments and computational fluid dynamics (CFD) methods were carried out to ensure the validity of the study, the results showed that the scroll inlet prototype cyclone separator with a helical angle of 150, inlet velocity of 10m/s, outlet diameter of 72 mm provides empirical values for pressure drop and the best particle separation efficiency for multi-parameter responses, further research can be done by modifying the shape and dimensions of the bottom outlet.
TL;DR: In this article , an enhanced firefly algorithm (EFA) was proposed to solve scheduling hybrid thermal, pumped-storage, and wind power plants in the presence of uncertainty caused by wind speed.
Abstract: This paper presents a novel method based on an enhanced firefly algorithm (EFA) to solve scheduling hybrid thermal, pumped-storage, and wind plants. Since the scheduling problem is inherently discrete, basic EFA and binary encoding/decoding techniques are used in the proposed EFA approach. Optimal power values of thermal and pumped-storage units are determined separately in the presence of uncertainty caused by wind speed. The proposed method is applied to a real plant, including four pumped-storage units, 34 thermal units with different characteristics, and one wind turbine plant. In addition, dynamic constraints of upstream and downstream sources and constraints regarding thermal and wind units are also considered for finding the optimal solution. In addition, the proposed EFA is successfully applied to a real plant, and the results are compared with those of the three available methods. The results show that the proposed method has converted to a more optimal cost than the other methods.
TL;DR: In this article , goal programming is applied to decide the number of kendang drums, minimum production cost, and time for each drum, and the result of this research is that CV. CV.
Abstract: Kendang djembe is a percussion instrument played by striking with the fingers and palms. The body of the kendang djembe is generally made of wood and shaped like a cup or mug, carved either by machine or traditionally only by hand. This problem affects the production costs, the employee working house, and the profit of kendang djembe. Customer orders and requirements determine the production process for kendang djembe. It leads to fluctuations in market demand, affecting production costs and the working hours of kendang djembe employees. As a result, employees work overtime when orders rush in, resulting in poor product finishes such as crude engraving and painting. This research aims to minimize the production cost of kendang djembe, maximize the employee working hours, and maximize the profit by using the goal programming method. Goal programming is applied to decide the number of kendang djembe, the minimum production cost, and the time for each kendang djembe. The result of this research is that CV. Maharani Abadi has to make 237 units of kendang djembe paintings, 1266 kendang djembe carvings, 870 kendang djembe painting carvings, and 91 kendang djembe deep carvings. CV. Maharani spent a production cost of Rp 399,413,400, with the employee working 1846.36 hours, and obtained a maximum profit of Rp 126,526,600. This research helps the company to avoid unprofitable options in the production process of kendang djembe.
TL;DR: In this article , the authors measured the effectiveness of the Semi-Autogenous Grinding SAG mill machine and determined the failure using the OEE and FMEA methods, and recommended to increase the number of equipment that aims to prolong the machine's age and accelerate production.
Abstract: The mining company uses a variety of grinding machines to process minerals, whereas the most common type of machine is the Semi-Autogenous Grinding SAG Mill machine. This machine is employed for the mining process of hard rock as raw material into gold, copper, and silver. However, the SAG Mill machines are often broken, even suddenly not working, with an average loss time of 97.30 hours which impacts a decrease in efficiency and production quality of up to 40%. It can cause losses that do not reach the production target. This research aims to measure the effectiveness of the SAG Mill machine and determine the failure using the OEE and FMEA methods. The results showed that the SAG Mill machine is still under standardized based on the Japan Institute of Plant Maintenance (JIPM), which is 85%. The FMEA method and RPN value apply to analyze downtime losses, and idling is the loss that highly affects the effectiveness of SAG Mill machines. Recommendations for the company are to increase the number of equipment that aims to prolong the machine's age and accelerate production. This research contributes to another solution to help maintenance managers by measuring the effectiveness and determining the failure of the SAG Mill machine
TL;DR: In this article , the authors explored the challenges and lessons learned in integrating a project management office (PMO) into the existing organizational structure of engineering-service contractor (ESC) companies in Trinidad and Tobago (T&T).
Abstract: This paper explores the challenges and lessons learned in integrating a project management office (PMO) into the existing organizational structure of engineering-service contractor (ESC) companies in Trinidad and Tobago (T&T). Although several T&T ESCs now boast of having a robust PMO, its implementation has been a difficult and expensive endeavor for most, persuading others to forego this. This disinclination is due to the lack of available insight and guidance on PMO implementation for ESCs operating in the Caribbean. Top management personnel and departmental managers from twenty-eight ESCs who played a direct role in the PMO incorporation at their organizations were polled in a self-report study which collected quantitative data via a questionnaire. Insights on their perceived PMO value, implementation weak and strong points, integration challenges and lessons learned were gathered and analyzed. The findings confirmed concurrence amongst all participating ESCs that PMO implementation bodes well for their strategic organizational goals. The biggest implementation challenges reported were creating a project management culture and realigning the power for resource management and allocation. Smoother integration was reported amongst companies that included suitable communication channels, pre-implementation planning, and project management training for PMO personnel into the process. For the findings varied across companies, this paper illustrates numerous areas of concern common to ESCs. There is no existing research on PMO implementation in T&T or Caribbean firms, and this paper provides foresight and direction for companies contemplating such endeavors.
TL;DR: ECPoC as mentioned in this paper uses ten criteria to evaluate and select a new block procedure in each round, and a set of optimal weights used for maximizing the network's decentralization level is identified through the use of evolutionary computation algorithms.
Abstract: Recently, blockchain technology has been applied in many domains in our life. Blockchain networks typically utilize a consensus protocol to achieve consistency among network nodes in a decentralized environment. Delegated Proof of Stake (DPoS) is a popular mechanism adopted in many networks such as BitShares, EOS, and Cardano because of its speed and scalability advantages. However, votes that come from nodes on a DPoS network tend to support a set of specific nodes that have a greater chance of becoming block producers after voting rounds. Therefore, only a small group of nodes can be selected to become block producers. To address this issue, we propose a new protocol called Evolutionary Computation-based Proof of Criteria (ECPoC), which uses ten criteria to evaluate and select a new block procedure in each round. Next, a set of optimal weights used for maximizing the network’s decentralization level is identified through the use of evolutionary computation algorithms. The experimental results show that our consensus significantly enhances the degree of decentralization in the selection process of witness nodes compared to DPoS. As a result, ECPoC facilitates fairness between nodes and creates momentum for blockchain network development