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In the era of the fourth industrial revolution, the international community is striving to establish a coordinated system to prevent fatal climate change in a global sense. As a result of such changes in business environments, a new issue, sustainability, has recently presented a paradigm shift and new research opportunity in which the theories and practices in traditional production and operations management are being reinterpreted and reapplied in relation to this emerging issue. Under this research background, we consider an optimal emission-trading problem under a cap-and-trade (CAT) emission regulation when the customers’ demand is given as an arbitrary probability distribution. Such a CAT approach to reduce the amount of emissions is a normative system for the sustainable production of manufacturing firms, which is also closely related to a well-known open innovation in literature of inventory management. Then, we formulate two stochastic inventory optimization models, which can be applied immediately for two famous CAT policies that exist in reality. In particular, our objective is to draw theoretical and practical implications for baseline credit emission regulations, which are innovative and government-led emission regulation policies, with a well-known newsvendor analysis. For our analytical results, we first show that our objective functions are piecewise linear and (quasi)-concave. Thus, it is found that there exists a unique optimal solution to the problem. Second, we successfully obtain the closed-form optimal solutions for the two models considered. Finally, we conduct a sensitivity analysis through a comparative static analysis to examine how the model parameters can affect the optimal solution in each model. All these analytical results and implications are consistent with previous studies in the literature, as well as with our insights for the models.
Sungyong Choi; KyungBae Park; And Sang-Oh Shim. The Optimal Emission Decisions of Sustainable Production with Innovative Baseline Credit Regulations. Sustainability 2019, 11, 1635 .
AMA StyleSungyong Choi, KyungBae Park, And Sang-Oh Shim. The Optimal Emission Decisions of Sustainable Production with Innovative Baseline Credit Regulations. Sustainability. 2019; 11 (6):1635.
Chicago/Turabian StyleSungyong Choi; KyungBae Park; And Sang-Oh Shim. 2019. "The Optimal Emission Decisions of Sustainable Production with Innovative Baseline Credit Regulations." Sustainability 11, no. 6: 1635.
This research addresses a specific issue in the field of operation scheduling. Even though there are lots of researches on the field of planning and scheduling, a specific scheduling problem is introduced here. We focus on the operation scheduling requirements that the Fourth Industrial Revolution has brought currently. From the point of view of open innovation, operation scheduling is known as the one that is using the Internet of Things, Cloud Computing, Big Data, and Mobile technology. To build proper operation systems under the Fourth Industrial Revolution, it is very essential to devise effective and efficient scheduling methodology to improve product quality, customer delivery, manufacturing flexibility, cost saving, and market competence. A scheduling problem on designated parallel equipments, where some equipments are grouped according to the recipe of lots, is considered. This implies that a lot associated with a specific recipe is preferred to be processed on an equipment among predetermined (designated) ones regardless of parallel ones. A setup operation occurs between different recipes of lots. In order to minimize completion time of the last lot, a scheduling algorithm is proposed. We conducted a simulation study with randomly generated problems, and the proposed algorithm has shown desirable and better performance that can be applied in real-time scheduling.
Sang-Oh Shim; KyungBae Park; Sungyong Choi. Sustainable Production Scheduling in Open Innovation Perspective under the Fourth Industrial Revolution. Journal of Open Innovation: Technology, Market, and Complexity 2018, 4, 42 .
AMA StyleSang-Oh Shim, KyungBae Park, Sungyong Choi. Sustainable Production Scheduling in Open Innovation Perspective under the Fourth Industrial Revolution. Journal of Open Innovation: Technology, Market, and Complexity. 2018; 4 (4):42.
Chicago/Turabian StyleSang-Oh Shim; KyungBae Park; Sungyong Choi. 2018. "Sustainable Production Scheduling in Open Innovation Perspective under the Fourth Industrial Revolution." Journal of Open Innovation: Technology, Market, and Complexity 4, no. 4: 42.
This study deals with a multi-level job scheduling problem in a single machine under processing time uncertainty. For the objectives of minimizing the total weighted tardiness of orders and the schedule deviation of the realized schedule from the baseline schedule, two surrogate measures for each of the two objectives are proposed to cope with the processing time uncertainty in the baseline scheduling phase. For the suggested surrogate measures, several optimal solution properties are developed to reduce the size of the solution space. Then, by using the solution properties a heuristic algorithm with two different order prioritization rules and a metaheuristic algorithm based on the discrete particle swarm optimization are developed for the order sequencing problem. Also, an iterative job sequencing algorithm is developed for the job sequencing problem that can be used for a given order sequence. From a series of computational experiments with a number of randomly generated problem instances with multiple bills of materials and normally distributed processing times of items, it is identified that the suggested metaheuristic algorithm with or without the iterative job sequencing algorithm shows good performance compared with the heuristic algorithm.
Byung Jun Joo; Sang-Oh Shim; Tay Jin Chua; Tian Xiang Cai. Multi-level job scheduling under processing time uncertainty. Computers & Industrial Engineering 2018, 120, 480 -487.
AMA StyleByung Jun Joo, Sang-Oh Shim, Tay Jin Chua, Tian Xiang Cai. Multi-level job scheduling under processing time uncertainty. Computers & Industrial Engineering. 2018; 120 ():480-487.
Chicago/Turabian StyleByung Jun Joo; Sang-Oh Shim; Tay Jin Chua; Tian Xiang Cai. 2018. "Multi-level job scheduling under processing time uncertainty." Computers & Industrial Engineering 120, no. : 480-487.
We consider a problem of scheduling jobs of two classes of urgencies in a two‐machine flowshop with the objective of minimizing total tardiness of one class for urgent jobs and the maximum completion time of the other class for non‐urgent jobs. Urgent jobs are an important consideration in the real manufacturing systems, but it has not been studied due to the difficulty of the problem. In this research, a branch‐and‐bound (B&B) algorithm is proposed through developing lower bounds, dominance properties, and heuristic algorithms for obtaining an initial feasible solution. To evaluate the performance of the proposed algorithms, computational experiments on randomly generated instances are performed. Results of the experiments show that the suggested B&B algorithm can solve problems with up to 20 jobs in a reasonable amount of CPU time.
Bongjoo Jeong; Yeong-Dae Kim; Sang-Oh Shim. Algorithms for a two‐machine flowshop problem with jobs of two classes. International Transactions in Operational Research 2018, 27, 3123 -3143.
AMA StyleBongjoo Jeong, Yeong-Dae Kim, Sang-Oh Shim. Algorithms for a two‐machine flowshop problem with jobs of two classes. International Transactions in Operational Research. 2018; 27 (6):3123-3143.
Chicago/Turabian StyleBongjoo Jeong; Yeong-Dae Kim; Sang-Oh Shim. 2018. "Algorithms for a two‐machine flowshop problem with jobs of two classes." International Transactions in Operational Research 27, no. 6: 3123-3143.
Scheduling problems for the sustainability of manufacturing firms in the era of the fourth industrial revolution is addressed in this research. In terms of open innovation, innovative production scheduling can be defined as scheduling using big data, cyber-physical systems, internet of things, cloud computing, mobile network, and so on. In this environment, one of the most important things is to develop an innovative scheduling algorithm for the sustainability of manufacturing firms. In this research, a flexible flowshop scheduling problem is considered with the properties of sequence-dependent setup and different process plans for jobs. In a flexible flowshop, there are serial workstations with multiple pieces of equipment that are able to process multiple lots simultaneously. Since the scheduling in this workshop is known to be extremely difficult, it is important to devise an efficient and effective scheduling algorithm. In this research, a heuristic algorithm is proposed based on a few dispatching rules and economic lot size model with the objective of minimizing total tardiness of orders. For the purposes of performance evaluation, a simulation study is conducted on randomly generated problem instances. The results imply that our proposed method outperforms the existing ones, and greatly enhances the sustainability of manufacturing firms.
Sang-Oh Shim; KyungBae Park; Sungyong Choi. Innovative Production Scheduling with Customer Satisfaction Based Measurement for the Sustainability of Manufacturing Firms. Sustainability 2017, 9, 2249 .
AMA StyleSang-Oh Shim, KyungBae Park, Sungyong Choi. Innovative Production Scheduling with Customer Satisfaction Based Measurement for the Sustainability of Manufacturing Firms. Sustainability. 2017; 9 (12):2249.
Chicago/Turabian StyleSang-Oh Shim; KyungBae Park; Sungyong Choi. 2017. "Innovative Production Scheduling with Customer Satisfaction Based Measurement for the Sustainability of Manufacturing Firms." Sustainability 9, no. 12: 2249.
We suggest a mixed integer programming model for solving a scheduling problem in a single machine shop. The scheduling problem considered here addresses two urgencies of jobs, i.e., urgent jobs and normal jobs, in which can be occurred in the real IT manufacturing firms, to minimize total tardiness for urgent ones and total completion time of normal ones. Two linear mathematical formulations by using time indexed methods are proposed for this problem and these are compared with the existing algorithms used in the real situation. Computational experiments with randomly generated instances are conducted and results of the experiments show that proposed time indexed formulation can obtain optimal solutions in shorter time than another mathematical formulation.
Bongjoo Jeong; Sang-Oh Shim; Sungyong Choi. Mathematical Programming Model for a Single Machine Scheduling in an IT Manufacturing Firms. Advanced Science Letters 2017, 23, 1705 -1708.
AMA StyleBongjoo Jeong, Sang-Oh Shim, Sungyong Choi. Mathematical Programming Model for a Single Machine Scheduling in an IT Manufacturing Firms. Advanced Science Letters. 2017; 23 (3):1705-1708.
Chicago/Turabian StyleBongjoo Jeong; Sang-Oh Shim; Sungyong Choi. 2017. "Mathematical Programming Model for a Single Machine Scheduling in an IT Manufacturing Firms." Advanced Science Letters 23, no. 3: 1705-1708.
This paper considers a two-machine re-entrant flowshop scheduling problem in which there are two classes of jobs with different urgencies, i.e., urgent jobs and normal (not urgent) jobs. The objective of this problem is minimizing total tardiness of one class of urgent jobs and maximum completion times of the other class of normal jobs. To solve this problem, a lower bound and several heuristic algorithms for the problem are proposed. To evaluate the performance of developed algorithms, computational experiments are performed on randomly generated problems, and results are reported with analysis. The suggested algorithms show better performances compared with the ones used in real manufacturing systems in terms of solution quality and computation time.
Bongjoo Jeong; Sang-Oh Shim. Heuristic algorithms for two-machine re-entrant flowshop scheduling problem with jobs of two classes. Journal of Advanced Mechanical Design, Systems, and Manufacturing 2017, 11, JAMDSM0062 -JAMDSM0062.
AMA StyleBongjoo Jeong, Sang-Oh Shim. Heuristic algorithms for two-machine re-entrant flowshop scheduling problem with jobs of two classes. Journal of Advanced Mechanical Design, Systems, and Manufacturing. 2017; 11 (5):JAMDSM0062-JAMDSM0062.
Chicago/Turabian StyleBongjoo Jeong; Sang-Oh Shim. 2017. "Heuristic algorithms for two-machine re-entrant flowshop scheduling problem with jobs of two classes." Journal of Advanced Mechanical Design, Systems, and Manufacturing 11, no. 5: JAMDSM0062-JAMDSM0062.
Sang-Oh Shim. Scheduling on a Flexible Job Shop with Setup Operation in IT Manufacturing Fabrication. Indian Journal of Science and Technology 2016, 9, 1 .
AMA StyleSang-Oh Shim. Scheduling on a Flexible Job Shop with Setup Operation in IT Manufacturing Fabrication. Indian Journal of Science and Technology. 2016; 9 (41):1.
Chicago/Turabian StyleSang-Oh Shim. 2016. "Scheduling on a Flexible Job Shop with Setup Operation in IT Manufacturing Fabrication." Indian Journal of Science and Technology 9, no. 41: 1.
In this paper, a technology for production scheduling is addressed for the sustainability and open innovation in a manufacturing business. Methodologies for scheduling jobs on parallel machines with the fixed processing property are devised. The fixed processing property, in which a group of specific jobs can be processed on the predetermined machine, can be found in most manufacturing systems due to the quality issues. Usually, even though parallel machines can process various types of jobs, the fixed processing is preferred as to not deteriorate products’ quality in real manufacturing systems. To minimize makespan of jobs, which is defined as the final completion time of all jobs, technology for production scheduling is developed. Several heuristic algorithms are devised for solving the problem and to evaluate performance of the suggested algorithms, a series of computational experiments is performed. Results show that better solutions are obtained by the suggested algorithms in a reasonable amount of computation time. That is, if the proposed technology is applied to the production scheduling system of a real manufacturing business, it can be expected that quantity and quality of the product will be enhanced since they are influenced by the production scheduling.
Sang-Oh Shim; KyungBae Park. Technology for Production Scheduling of Jobs for Open Innovation and Sustainability with Fixed Processing Property on Parallel Machines. Sustainability 2016, 8, 904 .
AMA StyleSang-Oh Shim, KyungBae Park. Technology for Production Scheduling of Jobs for Open Innovation and Sustainability with Fixed Processing Property on Parallel Machines. Sustainability. 2016; 8 (9):904.
Chicago/Turabian StyleSang-Oh Shim; KyungBae Park. 2016. "Technology for Production Scheduling of Jobs for Open Innovation and Sustainability with Fixed Processing Property on Parallel Machines." Sustainability 8, no. 9: 904.
The development of an integrated and personalized healthcare system is becoming an important issue in the modern healthcare industry. One of main objectives of integrated healthcare system is to effectively manage patients having chronic diseases that require long term care and its temporal information plays an important role to manage the statuses of diseases. Thus, a patient having chronic disease needs to visit the hospital periodically, which generates large volume of medical examination data. Among the various chronic diseases, metabolic syndrome (MS) has become a popular chronic disease in many countries. There have been efforts to develop an MS risk quantification and prediction model and to integrate it into personalized healthcare system, so as to predict the risk of having MS in the future. However, the development of methods for temporal progress management of metabolic syndrome has not been widely investigated. This paper proposes a method for identifying the temporal progress of MS patients' status based on the chronological clustering methodology. To investigate the temporal changes of disease status, we develop a chronological distance variance model that quantifies the difference of areal similarity degree (ASD) values between estimated and examined results of MS risk factors. We evaluate the clinical effectiveness of the temporal progress model by using sample subjects' examination results that have been measured for 10 years. We further elaborate the accuracy of the proposed temporal progress estimation method by using multiple linear regression method. Then, we develop a tier-based patients' MS status classification based on the chronological distance variance. The tier classification is based on the sensitivity for temporal change of MS status according to different values of control range of chronological distance variance. Our proposed temporal change identification method and patients' tier classification are expected to be incorporated with the integrated healthcare systems to help physicians with identifying the temporal progress of MS patients' health status and MS patients with self-management at home environments.
S. Jeong; C.-H. Youn; Y.-W. Kim; S.-O. Shim. Temporal progress model of metabolic syndrome for clinical decision support system. IRBM 2014, 35, 310 -320.
AMA StyleS. Jeong, C.-H. Youn, Y.-W. Kim, S.-O. Shim. Temporal progress model of metabolic syndrome for clinical decision support system. IRBM. 2014; 35 (6):310-320.
Chicago/Turabian StyleS. Jeong; C.-H. Youn; Y.-W. Kim; S.-O. Shim. 2014. "Temporal progress model of metabolic syndrome for clinical decision support system." IRBM 35, no. 6: 310-320.
Metabolic syndrome (MS) refers to a clustering of specific cardiovascular disease (CVD) risk factors whose underlying pathology is thought to be related to insulin resistance. The risk factors include insulin resistance, obesity, dyslipidemia, and hypertension and it is known to increase the risk for CVD and type II diabetes. Since MS helps to identify individuals at high risk for both CVD and type II diabetes, it has become a major public healthcare issue in many countries. There has been much effort to establish diagnostic criteria for MS, but the current diagnostic criteria of MS have weaknesses, such as binary decision based on diagnostic criteria, equal weight among risk factors, and difficulty in estimating the temporal progress of the risk factors. To resolve these problems, this paper proposes a risk quantification model for MS, which is based on areal similarity degree analysis between weighted radar charts comprising MS diagnostic criteria and examination results of risk factors. The clinical effectiveness of the proposed model is extensively evaluated by using data of a large number of subjects obtained from the third Korea National Health and Nutrition Examination Survey. The evaluation results show that the proposed model can quantify the risk of MS and effectively identify a group of subjects who might be classified into a potential risk group for having MS in the future.
Sangjin Jeong; Yu Mi Jo; Sang-Oh Shim; Yeon-Jung Choi; Chan-Hyun Youn. A Novel Model for Metabolic Syndrome Risk Quantification Based on Areal Similarity Degree. IEEE Transactions on Biomedical Engineering 2013, 61, 665 -679.
AMA StyleSangjin Jeong, Yu Mi Jo, Sang-Oh Shim, Yeon-Jung Choi, Chan-Hyun Youn. A Novel Model for Metabolic Syndrome Risk Quantification Based on Areal Similarity Degree. IEEE Transactions on Biomedical Engineering. 2013; 61 (3):665-679.
Chicago/Turabian StyleSangjin Jeong; Yu Mi Jo; Sang-Oh Shim; Yeon-Jung Choi; Chan-Hyun Youn. 2013. "A Novel Model for Metabolic Syndrome Risk Quantification Based on Areal Similarity Degree." IEEE Transactions on Biomedical Engineering 61, no. 3: 665-679.
Sang-Oh Shim; Yeong-Dae Kim. A branch and bound algorithm for an identical parallel machine scheduling problem with a job splitting property. Computers & Operations Research 2008, 35, 863 -875.
AMA StyleSang-Oh Shim, Yeong-Dae Kim. A branch and bound algorithm for an identical parallel machine scheduling problem with a job splitting property. Computers & Operations Research. 2008; 35 (3):863-875.
Chicago/Turabian StyleSang-Oh Shim; Yeong-Dae Kim. 2008. "A branch and bound algorithm for an identical parallel machine scheduling problem with a job splitting property." Computers & Operations Research 35, no. 3: 863-875.