Pub Date : 2018-05-25DOI: 10.1504/EJIE.2018.092008
Atıl Kurt, M. Azizoglu, F. C. Çetinkaya
This paper considers the blood distribution problem that includes irradiation centres, urgent demands, and product availability in Turkey, Central Anatolian Regional Blood Center of the Turkish Red Crescent. To address the problem, we develop a mixed integer linear program with two objectives: maximising the demand satisfaction and minimising total time travelled by the vehicles. We propose two decomposition-based heuristic solution approaches. The results of our experiments have revealed that the model cannot solve even small sized instances in reasonable times; however, the heuristic solution approaches are appropriate for solving complex real life problems. [Received: 5 May 2017; Revised: 21 December 2017; Accepted: 9 February 2018]
{"title":"Solution approaches to the blood distribution problem of the Turkish Red Crescent","authors":"Atıl Kurt, M. Azizoglu, F. C. Çetinkaya","doi":"10.1504/EJIE.2018.092008","DOIUrl":"https://doi.org/10.1504/EJIE.2018.092008","url":null,"abstract":"This paper considers the blood distribution problem that includes irradiation centres, urgent demands, and product availability in Turkey, Central Anatolian Regional Blood Center of the Turkish Red Crescent. To address the problem, we develop a mixed integer linear program with two objectives: maximising the demand satisfaction and minimising total time travelled by the vehicles. We propose two decomposition-based heuristic solution approaches. The results of our experiments have revealed that the model cannot solve even small sized instances in reasonable times; however, the heuristic solution approaches are appropriate for solving complex real life problems. [Received: 5 May 2017; Revised: 21 December 2017; Accepted: 9 February 2018]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"405-441"},"PeriodicalIF":1.0,"publicationDate":"2018-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.092008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43042933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-26DOI: 10.1504/EJIE.2018.090614
M. Brusco, T. R. Johns, R. Venkataraman
This paper evaluates the efficacy of LP-based working subsets for generalised set-covering formulations of personnel scheduling problems and presents a nearest-neighbour augmentation procedure for improving performance. Three experimental studies were completed in the evaluation process. In the first study, the LP-based working subset was sufficient to yield an optimal shift scheduling solution for 85% of the 24,300 test problems and the nearest-neighbour augmentation improved the percentage of optimal solutions to over 98%. The second study focused on more complex cyclic shift scheduling environments that permitted shift length, meal break and relief break flexibility. The adequacy of LP-based working subsets was supported by the provision of optimal shift scheduling solutions for 185 of 189 (98%) of the test problems. The third study examined a challenging tour scheduling environment for which globally-optimal benchmarks are not available. The superiority of the augmented LP-based working subset procedure was nevertheless evident, as it yielded better results than the (non-augmented) LP-based working subset for 92% of the test problems despite being constrained to only 40% of the allowed computation time for the non-augmented subsets. [Received 24 April 2017; Revised 25 August 2017; Revised 17 September 2017; Accepted 6 December 2017]
{"title":"LP-based working subsets for personnel scheduling: Evaluation and augmentation","authors":"M. Brusco, T. R. Johns, R. Venkataraman","doi":"10.1504/EJIE.2018.090614","DOIUrl":"https://doi.org/10.1504/EJIE.2018.090614","url":null,"abstract":"This paper evaluates the efficacy of LP-based working subsets for generalised set-covering formulations of personnel scheduling problems and presents a nearest-neighbour augmentation procedure for improving performance. Three experimental studies were completed in the evaluation process. In the first study, the LP-based working subset was sufficient to yield an optimal shift scheduling solution for 85% of the 24,300 test problems and the nearest-neighbour augmentation improved the percentage of optimal solutions to over 98%. The second study focused on more complex cyclic shift scheduling environments that permitted shift length, meal break and relief break flexibility. The adequacy of LP-based working subsets was supported by the provision of optimal shift scheduling solutions for 185 of 189 (98%) of the test problems. The third study examined a challenging tour scheduling environment for which globally-optimal benchmarks are not available. The superiority of the augmented LP-based working subset procedure was nevertheless evident, as it yielded better results than the (non-augmented) LP-based working subset for 92% of the test problems despite being constrained to only 40% of the allowed computation time for the non-augmented subsets. [Received 24 April 2017; Revised 25 August 2017; Revised 17 September 2017; Accepted 6 December 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"175-198"},"PeriodicalIF":1.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.090614","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47244604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-26DOI: 10.1504/EJIE.2018.090615
K. Cha-ume, N. Chiadamrong
This study finds a way to alleviate and predict the effects of uncertainty in a retail supply chain network through lateral transshipment policies. The study develops a simulation-based optimisation model using the ARENA and OptQuest optimisation tool, and proposes an improved application of the lateral transshipment policy, in addition to four existing policies, to solve such uncertainty. A series of experiments is performed, varying significant cost parameters to study their effects on the profit of the whole chain. In order to determine the best transshipment policy and predict its financial performance, a proposed meta-prediction model based on regression analysis is used to assist in making decisions on the implementation of different types of transshipment policies under various cost scenarios. The proposed methodology assists in decision making on the selection and management of a lateral transshipment policy for a retail supply chain network in a certain situation under an uncertain environment. [Received 20 March 2016; Revised 8 September 2016; Revised 7 December 2017; Accepted 13 December 2017]
{"title":"Meta-prediction model for introducing lateral transshipment policies in a retail supply chain network through regression analysis","authors":"K. Cha-ume, N. Chiadamrong","doi":"10.1504/EJIE.2018.090615","DOIUrl":"https://doi.org/10.1504/EJIE.2018.090615","url":null,"abstract":"This study finds a way to alleviate and predict the effects of uncertainty in a retail supply chain network through lateral transshipment policies. The study develops a simulation-based optimisation model using the ARENA and OptQuest optimisation tool, and proposes an improved application of the lateral transshipment policy, in addition to four existing policies, to solve such uncertainty. A series of experiments is performed, varying significant cost parameters to study their effects on the profit of the whole chain. In order to determine the best transshipment policy and predict its financial performance, a proposed meta-prediction model based on regression analysis is used to assist in making decisions on the implementation of different types of transshipment policies under various cost scenarios. The proposed methodology assists in decision making on the selection and management of a lateral transshipment policy for a retail supply chain network in a certain situation under an uncertain environment. [Received 20 March 2016; Revised 8 September 2016; Revised 7 December 2017; Accepted 13 December 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"199-232"},"PeriodicalIF":1.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.090615","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47130461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-26DOI: 10.1504/EJIE.2018.090617
M. Galetto, F. Franceschini, D. Maisano, L. Mastrogiacomo
Quality function deployment (QFD) is a management tool used for the design of new products/services and the related production/supply processes. One of the goals of the method is to translate the customer requirements (CRs) into measurable engineering characteristics (ECs) of the new product/service and prioritise them, basing on their relationships with CRs and the related importances. To this purpose, the current scientific literature encompasses several alternative approaches (the most used is the independent scoring method – ISM), in most of which cardinal properties are arbitrarily attributed to data collected on ordinal scales. This paper describes and discusses a new approach based on ME-MCDM (multi expert/multiple criteria decision making) techniques, which do not require any debatable ordinal to cardinal conversion. The theoretical principles and the robustness of the method are presented and tested through some application examples related to a well-known case study reported in the scientific literature. [Received 5 May 2015; Revised 7 November 2017; Accepted 9 November 2017]
{"title":"Engineering characteristics prioritisation in QFD using ordinal scales: a robustness analysis","authors":"M. Galetto, F. Franceschini, D. Maisano, L. Mastrogiacomo","doi":"10.1504/EJIE.2018.090617","DOIUrl":"https://doi.org/10.1504/EJIE.2018.090617","url":null,"abstract":"Quality function deployment (QFD) is a management tool used for the design of new products/services and the related production/supply processes. One of the goals of the method is to translate the customer requirements (CRs) into measurable engineering characteristics (ECs) of the new product/service and prioritise them, basing on their relationships with CRs and the related importances. To this purpose, the current scientific literature encompasses several alternative approaches (the most used is the independent scoring method – ISM), in most of which cardinal properties are arbitrarily attributed to data collected on ordinal scales. This paper describes and discusses a new approach based on ME-MCDM (multi expert/multiple criteria decision making) techniques, which do not require any debatable ordinal to cardinal conversion. The theoretical principles and the robustness of the method are presented and tested through some application examples related to a well-known case study reported in the scientific literature. [Received 5 May 2015; Revised 7 November 2017; Accepted 9 November 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"151-174"},"PeriodicalIF":1.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.090617","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42809734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-26DOI: 10.1504/EJIE.2018.090619
L. Nagarajan, S. Mahalingam, Selvakumar Gurusamy, V. Dharmaraj
The single row facility layout problem (SRFLP) is concerned with the arrangements of machineries in a single line for processing multiple products. This arrangement is termed as linear machine sequence (lms). The aim of the proposed work is to design a best lms that simultaneously minimises the objectives: the total flow distance of the products (D); and the total length of the flow line (L) needed for accommodating the machineries in the shop floor. Consideration of more than one objective in a multi-product environment in bi-objective single row facility layout problem (BOSRFLP) is an NP-hard problem. Hence, artificial bee colony (ABC) algorithm is applied to identify the best lms. The effectiveness of the proposed algorithm is verified by solving the problems discussed in the literature. Maximum of 37.54% reduction in total flow distance and 9.31% reduction in total length of the flow line are achieved by the proposed method. [Revise 21 September 2017; Received 27 November 2016; Accepted on 29 December 2017]
{"title":"Solution for bi-objective single row facility layout problem using artificial bee colony algorithm","authors":"L. Nagarajan, S. Mahalingam, Selvakumar Gurusamy, V. Dharmaraj","doi":"10.1504/EJIE.2018.090619","DOIUrl":"https://doi.org/10.1504/EJIE.2018.090619","url":null,"abstract":"The single row facility layout problem (SRFLP) is concerned with the arrangements of machineries in a single line for processing multiple products. This arrangement is termed as linear machine sequence (lms). The aim of the proposed work is to design a best lms that simultaneously minimises the objectives: the total flow distance of the products (D); and the total length of the flow line (L) needed for accommodating the machineries in the shop floor. Consideration of more than one objective in a multi-product environment in bi-objective single row facility layout problem (BOSRFLP) is an NP-hard problem. Hence, artificial bee colony (ABC) algorithm is applied to identify the best lms. The effectiveness of the proposed algorithm is verified by solving the problems discussed in the literature. Maximum of 37.54% reduction in total flow distance and 9.31% reduction in total length of the flow line are achieved by the proposed method. [Revise 21 September 2017; Received 27 November 2016; Accepted on 29 December 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"252-275"},"PeriodicalIF":1.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.090619","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44160206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-26DOI: 10.1504/EJIE.2018.090622
Changchun Liu, Qiang Wang, Xi Xiang, Li Zheng
The real time characteristic is a critical property of cyber-physical systems and the transmission tardiness introduced by the computer system can lead to a significant performance degradation. In order to improve the real-time performance, data aggregation is always employed during data transmission. This paper studies a hybrid two-stage batch scheduling problem in which a set of receiving sensors are assigned to collect the data at the first stage and an aggregation sensor is employed to receive the data from receiving sensors, fuse and transmit the data to the destination at the second stage. Two objectives, which are minimising the number of tardy tasks and the total transmission tardiness, are studied. Some analytical properties are proved and some algorithms are proposed to solve the problem. Extensive numerical experiments are conducted to test the performances of the proposed algorithms. [Received 27 July 2017; Revised 28 November 2017; Accepted 2 January 2018]
{"title":"Minimising tardiness in hybrid two-stage batch scheduling problem in cyber-physical systems","authors":"Changchun Liu, Qiang Wang, Xi Xiang, Li Zheng","doi":"10.1504/EJIE.2018.090622","DOIUrl":"https://doi.org/10.1504/EJIE.2018.090622","url":null,"abstract":"The real time characteristic is a critical property of cyber-physical systems and the transmission tardiness introduced by the computer system can lead to a significant performance degradation. In order to improve the real-time performance, data aggregation is always employed during data transmission. This paper studies a hybrid two-stage batch scheduling problem in which a set of receiving sensors are assigned to collect the data at the first stage and an aggregation sensor is employed to receive the data from receiving sensors, fuse and transmit the data to the destination at the second stage. Two objectives, which are minimising the number of tardy tasks and the total transmission tardiness, are studied. Some analytical properties are proved and some algorithms are proposed to solve the problem. Extensive numerical experiments are conducted to test the performances of the proposed algorithms. [Received 27 July 2017; Revised 28 November 2017; Accepted 2 January 2018]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"276-306"},"PeriodicalIF":1.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.090622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41862677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-03-26DOI: 10.1504/EJIE.2018.090616
F. Zahedi-Hosseini, A. Syntetos, P. Scarf
This paper develops a simulation model to determine the cost-optimum inspection policy for a multi-line production system taking account of simultaneous downtime. The machines in the multi-line system are subject to a two stage failure process that is modelled using the delay-time concept. Our study indicates that: consecutive inspection of lines with priority for failure repair is cost-optimal, with a cost reduction of 61% compared to a 'run-to-failure' policy; and maintainers need to be responsive to operational requirements. Our ideas are developed in the context of a case study of a plant with three parallel lines, one of which is on cold-standby. [Received 13 October 2016; Revised 29 April 2017; Revised 14 December 2017; Accepted 14 December 2017]
{"title":"Optimisation of inspection policy for multi-line production systems","authors":"F. Zahedi-Hosseini, A. Syntetos, P. Scarf","doi":"10.1504/EJIE.2018.090616","DOIUrl":"https://doi.org/10.1504/EJIE.2018.090616","url":null,"abstract":"This paper develops a simulation model to determine the cost-optimum inspection policy for a multi-line production system taking account of simultaneous downtime. The machines in the multi-line system are subject to a two stage failure process that is modelled using the delay-time concept. Our study indicates that: consecutive inspection of lines with priority for failure repair is cost-optimal, with a cost reduction of 61% compared to a 'run-to-failure' policy; and maintainers need to be responsive to operational requirements. Our ideas are developed in the context of a case study of a plant with three parallel lines, one of which is on cold-standby. [Received 13 October 2016; Revised 29 April 2017; Revised 14 December 2017; Accepted 14 December 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"233-251"},"PeriodicalIF":1.0,"publicationDate":"2018-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.090616","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43464083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-19DOI: 10.1504/EJIE.2018.089883
Bugra Alkan, D. Vera, Mussawar Ahmad, B. Ahmad, R. Harrison
Complexity in manufacturing systems still remains a challenge and leads to operational issues and increased production cost. In this paper, drivers of complexity and typical symptoms of complex manufacturing systems are identified. A comprehensive review of studies published within the last two decades to assess manufacturing system complexity are presented. The key contributions of this review are: 1) a classification of complexity assessment methods based on perceived complexity symptoms; 2) a comprehensive review of assessment methods with cross-evaluation to identify appropriate use based on available data; 3) recommendations for the wider academic and industrial community, based on research trends identified in the literature, as to how complexity assessment should be addressed in the future. It is concluded that the assessment of complexity is necessary so that it can be controlled effectively, however the industry suffers from a lack of practical tools to support in this endeavour. [Received 23 December 2016; Revised 18 August, 14 October 2017; Accepted 22 October, 2017]
{"title":"Complexity in manufacturing systems and its measures: a literature review","authors":"Bugra Alkan, D. Vera, Mussawar Ahmad, B. Ahmad, R. Harrison","doi":"10.1504/EJIE.2018.089883","DOIUrl":"https://doi.org/10.1504/EJIE.2018.089883","url":null,"abstract":"Complexity in manufacturing systems still remains a challenge and leads to operational issues and increased production cost. In this paper, drivers of complexity and typical symptoms of complex manufacturing systems are identified. A comprehensive review of studies published within the last two decades to assess manufacturing system complexity are presented. The key contributions of this review are: 1) a classification of complexity assessment methods based on perceived complexity symptoms; 2) a comprehensive review of assessment methods with cross-evaluation to identify appropriate use based on available data; 3) recommendations for the wider academic and industrial community, based on research trends identified in the literature, as to how complexity assessment should be addressed in the future. It is concluded that the assessment of complexity is necessary so that it can be controlled effectively, however the industry suffers from a lack of practical tools to support in this endeavour. [Received 23 December 2016; Revised 18 August, 14 October 2017; Accepted 22 October, 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"116-150"},"PeriodicalIF":1.0,"publicationDate":"2018-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.089883","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49286637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-19DOI: 10.1504/EJIE.2018.089876
Jae-Min Yu, Dong Ho Lee
This study addresses a job shop scheduling problem in which jobs are grouped into job families, but they are processed individually using their distinct routings. Unlike the previous studies, we consider a due-date-based objective of minimising the total family tardiness, i.e., sum of positive deviations between the due-dates and the completion times of job families. A mixed integer programming model is developed to represent the problem mathematically. Then, an optimal algorithm is proposed using the branch and bound technique while developing a job family-based lower bound. For practical applications up to large sized instances, two types of heuristics, modified shifting bottleneck and priority scheduling algorithms, are also proposed. To test the performances of the three types of solution algorithms, computational experiments were done on a number of test instances and the results are reported. [Received: 10 September 2016; Revised: 28 February 2017; Revised: 6 June 2017; Accepted: 22 August 2017]
{"title":"Solution algorithms to minimise the total family tardiness for job shop scheduling with job families","authors":"Jae-Min Yu, Dong Ho Lee","doi":"10.1504/EJIE.2018.089876","DOIUrl":"https://doi.org/10.1504/EJIE.2018.089876","url":null,"abstract":"This study addresses a job shop scheduling problem in which jobs are grouped into job families, but they are processed individually using their distinct routings. Unlike the previous studies, we consider a due-date-based objective of minimising the total family tardiness, i.e., sum of positive deviations between the due-dates and the completion times of job families. A mixed integer programming model is developed to represent the problem mathematically. Then, an optimal algorithm is proposed using the branch and bound technique while developing a job family-based lower bound. For practical applications up to large sized instances, two types of heuristics, modified shifting bottleneck and priority scheduling algorithms, are also proposed. To test the performances of the three types of solution algorithms, computational experiments were done on a number of test instances and the results are reported. [Received: 10 September 2016; Revised: 28 February 2017; Revised: 6 June 2017; Accepted: 22 August 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"1-23"},"PeriodicalIF":1.0,"publicationDate":"2018-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.089876","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47186754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-02-19DOI: 10.1504/EJIE.2018.089878
Yang-Byung Park, Sung-Joon Yoon, Jun-Su Yoo
This paper proposes a knowledge-based intelligent decision support system for operational risk management of global supply chains (DSSRMG), a full-phase system not yet treated in the literature. DSSRMG predicts the supply chain performance using the enhanced artificial neural network combined with particle swarm optimisation, infers the core risk source using a method based on principle component analysis, and evaluates risk mitigation alternatives using the digraph-matrix approach combined with principle component analysis. A methodology using an adaptive-network-based fuzzy inference system is suggested to construct the knowledge base for mitigation alternatives. An industrial example is used to illustrate the performance of DSSRMG. Computational experiments show that the techniques used for DSSRMG are excellent. Especially, the algorithm for selecting the useful operation indicators improves the performance prediction accuracy by 7.1% on average. DSSRMG provides supply chain managers with a practical tool to accurately predict and effectively control the operational risk. [Received: 9 March 2017; Revised: 22 July 2017; Accepted: 2 October 2017]
{"title":"Development of a knowledge-based intelligent decision support system for operational risk management of global supply chains","authors":"Yang-Byung Park, Sung-Joon Yoon, Jun-Su Yoo","doi":"10.1504/EJIE.2018.089878","DOIUrl":"https://doi.org/10.1504/EJIE.2018.089878","url":null,"abstract":"This paper proposes a knowledge-based intelligent decision support system for operational risk management of global supply chains (DSSRMG), a full-phase system not yet treated in the literature. DSSRMG predicts the supply chain performance using the enhanced artificial neural network combined with particle swarm optimisation, infers the core risk source using a method based on principle component analysis, and evaluates risk mitigation alternatives using the digraph-matrix approach combined with principle component analysis. A methodology using an adaptive-network-based fuzzy inference system is suggested to construct the knowledge base for mitigation alternatives. An industrial example is used to illustrate the performance of DSSRMG. Computational experiments show that the techniques used for DSSRMG are excellent. Especially, the algorithm for selecting the useful operation indicators improves the performance prediction accuracy by 7.1% on average. DSSRMG provides supply chain managers with a practical tool to accurately predict and effectively control the operational risk. [Received: 9 March 2017; Revised: 22 July 2017; Accepted: 2 October 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":"12 1","pages":"93-115"},"PeriodicalIF":1.0,"publicationDate":"2018-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.089878","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44021359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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