{"title":"The impact of online sales on centralised and decentralised dual-channel supply chains","authors":"I. Moon, S. P. Sarmah, Subrata Saha","doi":"10.1504/EJIE.2018.10011153","DOIUrl":"https://doi.org/10.1504/EJIE.2018.10011153","url":null,"abstract":"This paper studies a supply chain structure featuring two different types of distribution channels through which manufacturers sell products. The centralised and decentralised distribution channels considered in this study are affected by online sales outside the structured channels. In the centralised distribution channel, two retail stores located in geographically distinct markets are operated by a single owner. In the decentralised distribution channel, two retailers independently operate two retail stores. In the non-cooperative scenario, the manufacturer always prefers the decentralised distribution channel irrespective of whether an online channel is used. To achieve channel coordination, a revenue-sharing contract is applied, but it can be used to coordinate only the decentralised distribution system. Therefore, a modified revenue-sharing contract is proposed to coordinate the centralised distribution system. The analytical study reveals that without coordination among the channel members, the manufacturer always earns maximum profit in decentralised distribution systems. However, if the supply chain is coordinated, then the manufacturer receives more benefits from using the centralised distribution systems under certain conditions. Propositions are presented to describe the characteristics of distribution structures, and to provide meaningful management guidelines for coordinating them. Extensive numerical investigations are also presented. [Received 20 January 2016; Revised 13 December 2016, 9 March, 4 August 2017; Accepted 25 September 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2018-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48449000","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}
{"title":"A branch and bound algorithm for solving large-scale single-machine scheduling problems with non-identical release dates","authors":"S. H. Zegordi, M. Yavari","doi":"10.1504/EJIE.2018.089879","DOIUrl":"https://doi.org/10.1504/EJIE.2018.089879","url":null,"abstract":"In this paper, we have examined minimising the total completion times in a single-machine scheduling problem with non-identical job release dates. This problem is known to be strongly NP-hard. We have proposed an effective lower bound-based. Also, a near optimal heuristic has been presented that has an average gap of less than 0.077% from the optimum solution. Additionally, in 18% of the problem instances with up to 60 jobs, the upper bound value is equal to the lower bound value. Then we provide two dominance properties. Subsequently, the proposed lower bound, upper bound and dominance properties have been applied in the branch and bound method and have been tested in a wide range of instances. Computational experiments demonstrate the ability of the proposed method to solve hard and large-size problems with up to 130 jobs within a reasonable time. [Received 19 June 2015; Revised 26 November 2016; Revised 24 January 2017; Accepted 5 September 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2018-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2018.089879","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44104491","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}
{"title":"Forecast-corrected production-inventory control policy in unreliable manufacturing systems","authors":"Nan Li, F. Chan, S. Chung","doi":"10.1504/EJIE.2017.087677","DOIUrl":"https://doi.org/10.1504/EJIE.2017.087677","url":null,"abstract":"In traditional research on production-inventory control problems with failure-prone manufacturing systems, a stationary demand process is an essential assumption. However, such a situation may not be true. This study extends the hedging-point-based production-inventory control problem into the case with non-stationary demand. The demand forecasting process is simulated and categorised into two different cases. First of all, a two-level control policy is proposed to solve the problem with a Markov modulated Poisson demand process which is often used in qualitative forecasting. Then the quantitative forecasting process using time series methods is modelled and a forecast-corrected control policy is proposed accordingly. The impact of forecasting on the system performance is then investigated. An integrated simulation and experimental design method was adopted to solve the modified optimal control problem. The results show that the proposed control policy can outperform the traditional stationary policy when the forecasting error is limited to a certain level. [Received 29 August 2014; Revised 13 July 2015; Revised 12 April 2016; Revised 20 September 2016; Revised 21 September 2016; Accepted 30 March 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.087677","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44607552","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}
Faisal Aqlan, Abdulaziz Ahmed, O. Ashour, Abdulrahman Shamsan, M. Hamasha
{"title":"An approach for rush order acceptance decisions using simulation and multi-attribute utility theory","authors":"Faisal Aqlan, Abdulaziz Ahmed, O. Ashour, Abdulrahman Shamsan, M. Hamasha","doi":"10.1504/EJIE.2017.087680","DOIUrl":"https://doi.org/10.1504/EJIE.2017.087680","url":null,"abstract":"Rush orders are orders with shorter lead times and higher operating priorities compared to regular orders. A company may accept rush order, regardless of its capacity or raw material constraints, to maintain customer satisfaction and/or increase profit. On the other hand, rush orders can cause problems in managing production systems due to the unbalanced use of system resources. In this paper, discrete event simulation (DES) and multi-attribute utility theory (MAUT) are integrated to study the impact of rush orders on the performance of a hybrid push-pull production system. The proposed approach is used to identify the best acceptance levels of rush orders. Numerical results showed that prioritising customer orders based on their associated utilities can improve the performance of a production system. In addition, the best acceptance levels of rush orders can be determined by maximising the performance of the production system while considering production constraints. [Received 25 May 2015; Revised 1 August 2016; Revised 6 September 2016; Revised 3 March 2017; Accepted 5 June 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.087680","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46008874","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}
{"title":"A hybrid metaheuristic method for the deterministic and robust uncapacitated multiple allocation p-hub centre problem","authors":"Stefan Miskovic, Z. Stanimirović","doi":"10.1504/EJIE.2017.087705","DOIUrl":"https://doi.org/10.1504/EJIE.2017.087705","url":null,"abstract":"This study considers the well-known uncapacitated multiple allocation p-hub centre problem (UMApHCP) and introduces its robust variant (UMApHCP-R) by involving flow variations with unknown distributions. As a solution method to both UMApHCP and UMAPHCP-R, a hybrid metaheuristic algorithm (HMA) is proposed, which successfully combines particle swarm optimisation and a local search heuristic. Constructive elements of the HMA are adapted to the considered problems and its parameters are experimentally adjusted. Experimental results obtained for the UMApHCP show the superiority of the proposed HMA over the existing methods from the literature on standard hub instances in the sense of solution quality or running times. The results obtained by the HMA on large-scale hub instances with up to 900 nodes are also presented. The analysis of the HMA results for the UMApHCP-R on selected problem instances shows the impact of flow variations on the objective function value. [Received 11 September 2016; Revised 23 March 2017; Accepted 7 July 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.087705","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47432933","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}
{"title":"Manufacturing quality improvement and setup cost reduction in a vendor-buyer supply chain model","authors":"Arunava Majumder, Rekha Guchhait, B. Sarkar","doi":"10.1504/EJIE.2017.087678","DOIUrl":"https://doi.org/10.1504/EJIE.2017.087678","url":null,"abstract":"Quality improvement and setup cost reduction of any production system are endless procedure. Customer's demand is always intended to have the best quality product and the industries always try to improve the quality of products. This paper develops a two-echelon supply chain model with quality improvement of products and setup cost reduction under controllable lead time. The lead time demand follows a normal distribution and in the second case, it does not consider any specific distribution except a mean and standard deviation. Both models are solved analytically to obtain global solution. Two improved iterative algorithms are developed in order to obtain the optimal results of decision variables numerically to minimise the total system cost. The expected value of additional information is calculated to show the financial effect for collecting the information about lead time demand distribution. Some numerical examples and sensitivity analysis are given to illustrate the model. [Received 8 December 2016; Revised 27 March 2017; Accepted 21 April 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.087678","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49025054","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}
J. García-Alcaráz, A. Maldonado-Macías, G. A. Hernández, E. Jiménez-Macías, J. C. S. Muro, J. Blanco-Fernández
{"title":"Impact of human factor on flexibility and supply chain agility of La Rioja wineries","authors":"J. García-Alcaráz, A. Maldonado-Macías, G. A. Hernández, E. Jiménez-Macías, J. C. S. Muro, J. Blanco-Fernández","doi":"10.1504/EJIE.2017.087703","DOIUrl":"https://doi.org/10.1504/EJIE.2017.087703","url":null,"abstract":"Human factors play an important role in the success of companies, especially in the performance of production systems. In this research paper, we propose a structural equation model that measures the impact of four human factors (knowledge, abilities, skills, and availability) on production process flexibility and supply chain agility in the wine industry of La Rioja, Spain. The results obtained indicate that these human factors have a direct and positive impact on production process flexibility and supply chain agility. Likewise, they can be indirectly linked to supply chain agility through production process flexibility. Based on these findings, this research encourages La Rioja wineries to jointly work with viticulture and enology programs of Spanish universities. This collaboration would enhance the impact of human factors on the wine industry, which would in turn allow wineries to rapidly and more effectively respond to customer needs. [Received 6 November 2015; Revised 15 October 2016; Revised 7 March 2017; Accepted 10 July 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.087703","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48389604","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}
{"title":"Lot-sizing policies for defective and deteriorating items with time-dependent demand and trade credit","authors":"S. Tiwari, H. Wee, Sumon Sarkar","doi":"10.1504/EJIE.2017.087694","DOIUrl":"https://doi.org/10.1504/EJIE.2017.087694","url":null,"abstract":"This study investigates an inventory model with unreliable supply where each received lot may have random fraction of defective items with known distribution. Thus, item inspection becomes essential in all the situations, especially when the items are of deteriorating nature. Moreover, in today's competitive business world, organisations may use promotional tools in order to increase their sales. One such tool is permissible delay in payments where the buyer does not have to pay for the goods purchased until a prescribed period given by the supplier. For the case when both the demand and the price vary with time, we investigate the impact on the retailer's ordering policy for deteriorating items under permissible delay in payments. Numerical examples and sensitivity analysis are illustrated to provide some important managerial implications. [Received 26 December 2016; Revised 20 April 2017; Revised 5 June 2017; Revised 3 July 2017; Accepted 11 July 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.087694","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47869656","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}
{"title":"Aggregation methodologies for perishability management in production and distribution system","authors":"Minh Ngoc, N. Nananukul","doi":"10.1504/EJIE.2017.086187","DOIUrl":"https://doi.org/10.1504/EJIE.2017.086187","url":null,"abstract":"An existing integrated model such as the production-inventory-routing-problem (PIDRP) can be used to generate operational decision in the planning horizon. However, for certain products, such as food, freshness of the product are also an important factor to be considered. Typically, determining the solutions for large instances of PIDRP is not possible. The contribution of this research is to propose two aggregation techniques that can manage large instances of PIDRP that consider perishability of products. The first technique is based on a clustering algorithm that considers constraints from delivery capacity. The second technique is a tailored aggregation for producing subsets of products that can be ordered jointly. Computational results show that the proposed techniques can be used to reduce problem size while maintaining good quality solution within acceptable run time. The gaps of the solutions for problem sets up to 30 retailers, 20 products and eight periods are less than 5%. [Received 8 December 2016; Revised 27 March 2017; Accepted 21 April 2017[","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.086187","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42463659","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}
{"title":"Minimal production level and reliability measurement for a maintainable production system under demand and budget constraints","authors":"Cheng-Ta Yeh, P. Chang, Chin Yeu Chen","doi":"10.1504/EJIE.2017.086185","DOIUrl":"https://doi.org/10.1504/EJIE.2017.086185","url":null,"abstract":"This paper proposes two performance indicators, a minimal production level for demand D and maintenance budget B, and maintenance reliability for a maintainable production system (MPS) under both preventive and perfect maintenance consideration. The MPS owns the features of stochastic capacity and reworking action. The minimal production level for D and B is the minimal state of MPS fulfilling D subject to B. The maintenance reliability is defined as the probability that the MPS can successfully process D subject to B. The first indicator is regarded as the lowest acceptable point to repair the MPS; the other is adopted to measure the current performance of the MPS and can be a basis for production improvement. A developed procedural solution integrating a maintenance model and an activity-on-vertex predecessor-set technique is validated via a case of printed circuit board production to determine both indicators. [Received 22 July 2015; Revised 30 May 2016; Accepted 17 April 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.086185","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48581933","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}