Pub Date : 2020-02-10DOI: 10.1504/ejie.2020.10026811
H. Öztürk
This paper assumes that there may be some defective items in the various lots of an ordered shipment and chooses a sub-lot inspection policy. Another assumption that this paper makes is that a shipment is sent by a distant supplier and, therefore, the replacement of the defective items is not economical if an additional order is given to the same supplier. This paper incorporates misclassification errors, which are of two types: type 1 and type 2. In order to deal with the received defective items in the shipment, two cases are discussed in this study. The first case is to send them back to the repair shop to be reworked, whereas in the second case, those defective items are sold and replaced with perfect items by buying at a higher cost from a local supplier. For each case, a mathematical model is developed, and an example is solved. The results show a close connection between the optimal order size and sample size, which can be adjusted to maximise the total profit. The results also indicate that the local purchase of replacements for defective items tends to produce greater total profit than reworking them. [Received: 26 June 2018; Accepted: 17 May 2019]
{"title":"Economic order quantity models for the shipment containing defective items with inspection errors and a sub-lot inspection policy","authors":"H. Öztürk","doi":"10.1504/ejie.2020.10026811","DOIUrl":"https://doi.org/10.1504/ejie.2020.10026811","url":null,"abstract":"This paper assumes that there may be some defective items in the various lots of an ordered shipment and chooses a sub-lot inspection policy. Another assumption that this paper makes is that a shipment is sent by a distant supplier and, therefore, the replacement of the defective items is not economical if an additional order is given to the same supplier. This paper incorporates misclassification errors, which are of two types: type 1 and type 2. In order to deal with the received defective items in the shipment, two cases are discussed in this study. The first case is to send them back to the repair shop to be reworked, whereas in the second case, those defective items are sold and replaced with perfect items by buying at a higher cost from a local supplier. For each case, a mathematical model is developed, and an example is solved. The results show a close connection between the optimal order size and sample size, which can be adjusted to maximise the total profit. The results also indicate that the local purchase of replacements for defective items tends to produce greater total profit than reworking them. [Received: 26 June 2018; Accepted: 17 May 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123418089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-07DOI: 10.1504/ejie.2020.10025693
Rodrigo Barbosa Correa, A. Mercado, María Jubiz Diaz, Ricardo R. Ramos
This paper presents an approach for determining the personnel capacity levels of a call centre for a telecommunication company. The objective is to determine the staffing levels required to meet a desired service level at a minimum cost. First, data of the number of different requests were analysed to estimate hourly workload requirements. Then, an aggregate planning model were implemented to obtain an initial solution of the staffing levels considering workforce costs, service level, personnel hiring/migration and work supplements. These results were input of a discrete-event simulation model to assess the system performance based on queuing characteristics, demand variability and resources utilisation. Alternative schedules and capacity levels were evaluated to outperform current service quality and a better match with the demand variability. Proposed options provided better results with lower waiting times and more balanced resource utilisation. The approach is useful for planning capacity levels in projects and locating new centres. [Submitted: 18 June 2018; Accepted: 15 March 2019]
{"title":"Establishing call-centre staffing levels using aggregate planning and simulation approach","authors":"Rodrigo Barbosa Correa, A. Mercado, María Jubiz Diaz, Ricardo R. Ramos","doi":"10.1504/ejie.2020.10025693","DOIUrl":"https://doi.org/10.1504/ejie.2020.10025693","url":null,"abstract":"This paper presents an approach for determining the personnel capacity levels of a call centre for a telecommunication company. The objective is to determine the staffing levels required to meet a desired service level at a minimum cost. First, data of the number of different requests were analysed to estimate hourly workload requirements. Then, an aggregate planning model were implemented to obtain an initial solution of the staffing levels considering workforce costs, service level, personnel hiring/migration and work supplements. These results were input of a discrete-event simulation model to assess the system performance based on queuing characteristics, demand variability and resources utilisation. Alternative schedules and capacity levels were evaluated to outperform current service quality and a better match with the demand variability. Proposed options provided better results with lower waiting times and more balanced resource utilisation. The approach is useful for planning capacity levels in projects and locating new centres. [Submitted: 18 June 2018; Accepted: 15 March 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133684180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-27DOI: 10.1504/ejie.2019.104312
Manuel J. Campuzano, A. Carrión, Jaime Mosquera
This paper proposes a new double sampling scheme for c control chart (DS-c), which was designed to improve the performance of c chart or to reduce the inspection cost. The mathematical expression required to do an exact evaluation of ARL and ASN is deduced. Further, a bi-objective genetic algorithm is implemented to obtain the optimal design of the DS-c scheme. This optimisation is aimed to simultaneously minimising the error probability type II and the ASN, guaranteeing a desired level for the error probability type I. A performance comparison between the double sampling (DS), fixed parameters (FP), variable simple size (VSS) and exponential weighted moving average (EWMA) schemes for the c chart is carried out. The comparison shows that with the implementation of DS-c scheme is obtained a significant reduction of the out of control ARL with a lower ASN respect to FP and a better ARL profile than VSS and EWMA. [Received: 4 February 2018; Accepted: 1 February 2019]
{"title":"Characterisation and optimal design of a new double sampling c chart","authors":"Manuel J. Campuzano, A. Carrión, Jaime Mosquera","doi":"10.1504/ejie.2019.104312","DOIUrl":"https://doi.org/10.1504/ejie.2019.104312","url":null,"abstract":"This paper proposes a new double sampling scheme for c control chart (DS-c), which was designed to improve the performance of c chart or to reduce the inspection cost. The mathematical expression required to do an exact evaluation of ARL and ASN is deduced. Further, a bi-objective genetic algorithm is implemented to obtain the optimal design of the DS-c scheme. This optimisation is aimed to simultaneously minimising the error probability type II and the ASN, guaranteeing a desired level for the error probability type I. A performance comparison between the double sampling (DS), fixed parameters (FP), variable simple size (VSS) and exponential weighted moving average (EWMA) schemes for the c chart is carried out. The comparison shows that with the implementation of DS-c scheme is obtained a significant reduction of the out of control ARL with a lower ASN respect to FP and a better ARL profile than VSS and EWMA. [Received: 4 February 2018; Accepted: 1 February 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128708331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-27DOI: 10.1504/EJIE.2019.10021944
Naveen Virmani, Vikram Sharma
Nowadays, market is very competitive. Industries are required to make changes in the production system quickly so as to meet the fluctuating needs of customers. Also, the components or product made should be of good quality at reasonable cost. To accomplish this task, industries are required to have state of art facilities like flexible manufacturing system (FMS), robotics, programmable logic controller (PLC), electric discharge machining (EDM), etc. In this paper, leagile system, i.e., combination of lean and agile system has been discussed. The concept of leagile manufacturing tries to reduce the cost of the product to minimum possible level and reduces the cycle time so that the finished products can be delivered to the customer as quickly as possible. In this paper, leagile enablers have been found out through literature review and in discussion with experts. Interpretive structural modelling technique (ISM) has been applied to find the relationship between these enablers and for constructing digraph. [Received: 28 March 2018; Accepted: 1 January 2019]
{"title":"Prioritization and Assessment of leagile manufacturing enablers using Interpretive Structural Modeling (ISM) approach","authors":"Naveen Virmani, Vikram Sharma","doi":"10.1504/EJIE.2019.10021944","DOIUrl":"https://doi.org/10.1504/EJIE.2019.10021944","url":null,"abstract":"Nowadays, market is very competitive. Industries are required to make changes in the production system quickly so as to meet the fluctuating needs of customers. Also, the components or product made should be of good quality at reasonable cost. To accomplish this task, industries are required to have state of art facilities like flexible manufacturing system (FMS), robotics, programmable logic controller (PLC), electric discharge machining (EDM), etc. In this paper, leagile system, i.e., combination of lean and agile system has been discussed. The concept of leagile manufacturing tries to reduce the cost of the product to minimum possible level and reduces the cycle time so that the finished products can be delivered to the customer as quickly as possible. In this paper, leagile enablers have been found out through literature review and in discussion with experts. Interpretive structural modelling technique (ISM) has been applied to find the relationship between these enablers and for constructing digraph. [Received: 28 March 2018; Accepted: 1 January 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123222293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-27DOI: 10.1504/ejie.2019.104280
Xue-Yi Ai, Jin Long Zhang, D. Song, Lin Wang
In this paper, we extend the existing stochastic joint replenishment model to a more realistic condition by considering uncertainties in lead-time and effective investment to reduce the major ordering cost. The aim is to determine the optimal strict cyclic replenishment policy and the optimal major ordering cost simultaneously to minimise the total cost. The objective cost function is approximated by expressing one element of the cost function as a Taylor series expansion. A bounds-based heuristic algorithm is then developed to solve the proposed model. The performance of the algorithm and the quality of the approximation are examined by computational experiments. The results of the models without considering uncertainty and ordering cost reduction are presented to illustrate the effectiveness of the proposed model. Experimentation and analysis of results demonstrate that the standard deviation of lead-time has a significant effect on the system. [Received: 21 December, 2016; Revised: 29 July 2017; Revised: 29 December 2017; Revised: 30 September 2018; Revised: 17 November 2018; Accepted: 26 January 2019]
{"title":"Modelling and optimising the multi-item stochastic joint replenishment problem with uncertain lead-time and controllable major ordering cost","authors":"Xue-Yi Ai, Jin Long Zhang, D. Song, Lin Wang","doi":"10.1504/ejie.2019.104280","DOIUrl":"https://doi.org/10.1504/ejie.2019.104280","url":null,"abstract":"In this paper, we extend the existing stochastic joint replenishment model to a more realistic condition by considering uncertainties in lead-time and effective investment to reduce the major ordering cost. The aim is to determine the optimal strict cyclic replenishment policy and the optimal major ordering cost simultaneously to minimise the total cost. The objective cost function is approximated by expressing one element of the cost function as a Taylor series expansion. A bounds-based heuristic algorithm is then developed to solve the proposed model. The performance of the algorithm and the quality of the approximation are examined by computational experiments. The results of the models without considering uncertainty and ordering cost reduction are presented to illustrate the effectiveness of the proposed model. Experimentation and analysis of results demonstrate that the standard deviation of lead-time has a significant effect on the system. [Received: 21 December, 2016; Revised: 29 July 2017; Revised: 29 December 2017; Revised: 30 September 2018; Revised: 17 November 2018; Accepted: 26 January 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128668666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-27DOI: 10.1504/ejie.2019.10026000
Chatdanai Kaorapapong, P. Yenradee
In practice, companies with dominant power influence partner operations for their benefits. This paper proposes the supply chain (SC) planning models that determine the optimal sale, pricing, production, and inventory plans of each SC member based on the dominant policy. The theoretical contributions of this paper include a development of linear mathematical functions and explicitly considering the inventory turnover as one of the business performance measures in addition to profit and revenue. The fuzzy multi-objective linear programming models (FMOLP) under dominant systems are developed. A case study in plastic fashion accessory industry in Thailand is performed. The performance measures are translated into satisfaction levels and plotted in a radar chart with an area of possibility, which clearly shows the sensitivity degree of uncertainty. Practical contribution is that this paper recommends suitable pricing and inventory plans based on the dominant policy. [Submitted: 15 August 2018; Accepted: 18 March 2019]
{"title":"Compromised supply chain planning under dominant systems with inventory policies and cost uncertainty","authors":"Chatdanai Kaorapapong, P. Yenradee","doi":"10.1504/ejie.2019.10026000","DOIUrl":"https://doi.org/10.1504/ejie.2019.10026000","url":null,"abstract":"In practice, companies with dominant power influence partner operations for their benefits. This paper proposes the supply chain (SC) planning models that determine the optimal sale, pricing, production, and inventory plans of each SC member based on the dominant policy. The theoretical contributions of this paper include a development of linear mathematical functions and explicitly considering the inventory turnover as one of the business performance measures in addition to profit and revenue. The fuzzy multi-objective linear programming models (FMOLP) under dominant systems are developed. A case study in plastic fashion accessory industry in Thailand is performed. The performance measures are translated into satisfaction levels and plotted in a radar chart with an area of possibility, which clearly shows the sensitivity degree of uncertainty. Practical contribution is that this paper recommends suitable pricing and inventory plans based on the dominant policy. [Submitted: 15 August 2018; Accepted: 18 March 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123528558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-27DOI: 10.1504/ejie.2019.10026070
T. V. Deepthi, K. Ramakotaiah, V. Manupati, Chaitanya Gangal
Seru production systems implement reconfiguration of traditional assembly lines to a flexible cell system that aim at reducing the required workforce while at the same time augmenting the productivity manifold. For evaluating the overall performance improvement, cell formatting and assigning workers to serus takes form of a complicated decision problem. In this paper, with the objective of reducing the total cost for training the worker, minimising the processing time and the total throughput time, mathematical insights on the solution space of a multi-objective line-cell conversion model are identified, in turn proving it to be an NP-hard model. By applying the proposed heuristic algorithm on several numerical simulations, a Pareto-optimal solution of this multi-objective model is obtained. With experimental results and comparative studies, the proposed approach proves its effectiveness that may lead to further improvement in seru production systems competitive advantage to cope with fluctuating market demands by enhancing the flexibility as well as the efficiency of the system. [Submitted: 18 June 2016; Revised 29: August 2017; Revised: 25 August 2018; Revised: 5 December 2018; Accepted: 8 January 2019]
{"title":"Investigating the performance improvement by conversion of assembly line configuration to a pure cell system in manufacturing industry","authors":"T. V. Deepthi, K. Ramakotaiah, V. Manupati, Chaitanya Gangal","doi":"10.1504/ejie.2019.10026070","DOIUrl":"https://doi.org/10.1504/ejie.2019.10026070","url":null,"abstract":"Seru production systems implement reconfiguration of traditional assembly lines to a flexible cell system that aim at reducing the required workforce while at the same time augmenting the productivity manifold. For evaluating the overall performance improvement, cell formatting and assigning workers to serus takes form of a complicated decision problem. In this paper, with the objective of reducing the total cost for training the worker, minimising the processing time and the total throughput time, mathematical insights on the solution space of a multi-objective line-cell conversion model are identified, in turn proving it to be an NP-hard model. By applying the proposed heuristic algorithm on several numerical simulations, a Pareto-optimal solution of this multi-objective model is obtained. With experimental results and comparative studies, the proposed approach proves its effectiveness that may lead to further improvement in seru production systems competitive advantage to cope with fluctuating market demands by enhancing the flexibility as well as the efficiency of the system. [Submitted: 18 June 2016; Revised 29: August 2017; Revised: 25 August 2018; Revised: 5 December 2018; Accepted: 8 January 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"26 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131805503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-02DOI: 10.1504/EJIE.2019.10022888
S. Kır, Harun Resit Yazgan
This paper presents a hierarchical approach, which consists of a two-stage genetic algorithm and a mixed integer linear programming, for a heterogeneous three-dimensional pallet loading problem in consideration of the rotation, the relative positioning, the load-bearing strength and the fragility constraints. Stage #1 of the proposed two-stage genetic algorithm provides to reduce the number of items to be packed by combining similar items based on a stack-building approach. And, stage #2 provides to estimate the number of required free pallets. After that, the proposed mixed integer linear programming solves the problem considering the findings of the proposed two-stage genetic algorithm. The proposed hierarchical approach was tested on well-known instances leading to favourable results and compared with a decent solution approach. In addition, a case study was presented. [Received: 7 July 2018; Revised: 20 November 2018; Accepted: 25 January 2019]
{"title":"A novel hierarchical approach for a heterogeneous 3D pallet loading problem subject to factual loading and delivery constraints","authors":"S. Kır, Harun Resit Yazgan","doi":"10.1504/EJIE.2019.10022888","DOIUrl":"https://doi.org/10.1504/EJIE.2019.10022888","url":null,"abstract":"This paper presents a hierarchical approach, which consists of a two-stage genetic algorithm and a mixed integer linear programming, for a heterogeneous three-dimensional pallet loading problem in consideration of the rotation, the relative positioning, the load-bearing strength and the fragility constraints. Stage #1 of the proposed two-stage genetic algorithm provides to reduce the number of items to be packed by combining similar items based on a stack-building approach. And, stage #2 provides to estimate the number of required free pallets. After that, the proposed mixed integer linear programming solves the problem considering the findings of the proposed two-stage genetic algorithm. The proposed hierarchical approach was tested on well-known instances leading to favourable results and compared with a decent solution approach. In addition, a case study was presented. [Received: 7 July 2018; Revised: 20 November 2018; Accepted: 25 January 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124086688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-02DOI: 10.1504/ejie.2019.102158
Jae-Dong Hong, Ki-Young Jeong
Emergency events such as natural disasters or terrorist attacks seem to occur anywhere and tend to increase. This paper studies a humanitarian supply chain network (HTSCN) design problem in a pre-disaster scenario, which consists of finding the optimal emergency response facility (ERF) locations and allocation scheme of humanitarian supplies through ERFs, where all ERFs are under the risk of disruptions. Naturally, this type of design problem should deal with multiple goals. An innovative two-step framework of designing efficient HTSCN by combining multi-objective programming (MOP) models with data envelopment analysis (DEA) is proposed. A case study using the historical data on the disasters in South Carolina, USA is presented to illustrate the effectiveness and efficiency of the proposed combining framework. The case study demonstrates that the proposed procedure would help practitioners and researchers generate a finer evaluation of efficiency and would provide a benchmarking methodology for designing HTSCN system. [Received: 22 October 2017; Revised: 9 April 2018; Revised: 15 October 2018; Revised: 22 December 2018; Accepted: 26 January 2019]
{"title":"Humanitarian supply chain network design using data envelopment analysis and multi-objective programming models","authors":"Jae-Dong Hong, Ki-Young Jeong","doi":"10.1504/ejie.2019.102158","DOIUrl":"https://doi.org/10.1504/ejie.2019.102158","url":null,"abstract":"Emergency events such as natural disasters or terrorist attacks seem to occur anywhere and tend to increase. This paper studies a humanitarian supply chain network (HTSCN) design problem in a pre-disaster scenario, which consists of finding the optimal emergency response facility (ERF) locations and allocation scheme of humanitarian supplies through ERFs, where all ERFs are under the risk of disruptions. Naturally, this type of design problem should deal with multiple goals. An innovative two-step framework of designing efficient HTSCN by combining multi-objective programming (MOP) models with data envelopment analysis (DEA) is proposed. A case study using the historical data on the disasters in South Carolina, USA is presented to illustrate the effectiveness and efficiency of the proposed combining framework. The case study demonstrates that the proposed procedure would help practitioners and researchers generate a finer evaluation of efficiency and would provide a benchmarking methodology for designing HTSCN system. [Received: 22 October 2017; Revised: 9 April 2018; Revised: 15 October 2018; Revised: 22 December 2018; Accepted: 26 January 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124009631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-08-02DOI: 10.1504/EJIE.2019.10022896
H. Soroush, F. Almathkour
This paper addresses the problem of minimising the variance of job completion times in a deterministic single-machine scheduling system. Minimising completion time variance is an appropriate objective in scheduling environments where service uniformity is essential. Due to the NP-hard nature of the problem, various heuristics have been presented to obtain a near-optimal solution. In this paper, we introduce a new heuristic based on some powerful precedence (dominance) relation structures, including the concepts of permanent and temporary precedence (dominance) relationships, to determine the positions of adjacent and non-adjacent jobs in a sequence. Our computational experiments demonstrate that the proposed heuristic significantly outperforms the existing ones in deriving the optimal or near-optimal solutions for three well-known sets of benchmark problems and some large randomly generated instances. [Received: 5 August 2018; Revised: 24 December 2018; Accepted: 23 January 2019]
{"title":"A dominance-based heuristic to minimise completion time variance in a single machine system","authors":"H. Soroush, F. Almathkour","doi":"10.1504/EJIE.2019.10022896","DOIUrl":"https://doi.org/10.1504/EJIE.2019.10022896","url":null,"abstract":"This paper addresses the problem of minimising the variance of job completion times in a deterministic single-machine scheduling system. Minimising completion time variance is an appropriate objective in scheduling environments where service uniformity is essential. Due to the NP-hard nature of the problem, various heuristics have been presented to obtain a near-optimal solution. In this paper, we introduce a new heuristic based on some powerful precedence (dominance) relation structures, including the concepts of permanent and temporary precedence (dominance) relationships, to determine the positions of adjacent and non-adjacent jobs in a sequence. Our computational experiments demonstrate that the proposed heuristic significantly outperforms the existing ones in deriving the optimal or near-optimal solutions for three well-known sets of benchmark problems and some large randomly generated instances. [Received: 5 August 2018; Revised: 24 December 2018; Accepted: 23 January 2019]","PeriodicalId":314867,"journal":{"name":"European J. of Industrial Engineering","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115652338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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