Pub Date : 2017-08-31DOI: 10.1504/EJIE.2017.086178
D. Shishebori, M. Karimi-Nasab, L. Snyder
This paper considers the reliable capacitated logistics network design problem (RCLNDP) with system disruptions, which is concerned with locating facilities, constructing transportation links, and allocating their capacities to customers in order to satisfy the demand with minimum expected total cost. Both the facilities and the transportation links are subject to random disruptions, and the expected total cost accounts for the costs of facility location, link construction, and flows in both normal and disrupted conditions. We model this problem as a two-stage stochastic program in which the decision maker establishes plans for facility location and link construction in the first stage (before disruptions are realised) and may choose link flows in the second stage. This is a large-scale mixed-integer optimisation problem and is therefore difficult to solve. Hence, we propose an efficient two-phase heuristic with three possible initial solution-generation methods. [Received 1 November 2015; Revised 3 March 2016; Revised 22 May 2016; Revised 8 June 2016; Accepted 10 June 2016]
{"title":"A two-phase heuristic algorithm for designing reliable capacitated logistics networks under disruptions","authors":"D. Shishebori, M. Karimi-Nasab, L. Snyder","doi":"10.1504/EJIE.2017.086178","DOIUrl":"https://doi.org/10.1504/EJIE.2017.086178","url":null,"abstract":"This paper considers the reliable capacitated logistics network design problem (RCLNDP) with system disruptions, which is concerned with locating facilities, constructing transportation links, and allocating their capacities to customers in order to satisfy the demand with minimum expected total cost. Both the facilities and the transportation links are subject to random disruptions, and the expected total cost accounts for the costs of facility location, link construction, and flows in both normal and disrupted conditions. We model this problem as a two-stage stochastic program in which the decision maker establishes plans for facility location and link construction in the first stage (before disruptions are realised) and may choose link flows in the second stage. This is a large-scale mixed-integer optimisation problem and is therefore difficult to solve. Hence, we propose an efficient two-phase heuristic with three possible initial solution-generation methods. [Received 1 November 2015; Revised 3 March 2016; Revised 22 May 2016; Revised 8 June 2016; Accepted 10 June 2016]","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.2017.086178","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43367819","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 : 2017-08-31DOI: 10.1504/EJIE.2017.086184
Faisal Aqlan
Inventory management in today's complex manufacturing environments has become increasingly challenging. Ineffective management of inventory can lead to material shortages, excessive inventories, long lead times, waste of space, and poor customer service. Nowadays, various companies are using information systems to establish effective linkages to suppliers, customers, and other agents in the supply chain. These information systems include comprehensive data warehouses that integrate operational data within the supply chain including part usage, customer demand, defect rates, etc. The data can be used in analytics models to improve warehouse operations and inventory management. In this research, an approach is proposed for warehouse inventory management based on part clustering. The proposed approach categorises inventory parts based on their pick frequency, age, price, and sensitivity to transportation. Part grouping helps the decision makers to identify whether to keep the part in the warehouse, move it to an offsite inventory storage, or scrap it. The approach also determines when and how many parts should be moved from the offsite storage to the internal warehouse in order to balance the inventory and minimise the transportation costs. Dynamic reports are generated on a regular basis to effectively manage the inventory. [Received 3 September 2016; Revised 9 March 2017; Accepted 13 March 2017]
{"title":"Dynamic clustering of inventory parts to enhance warehouse management","authors":"Faisal Aqlan","doi":"10.1504/EJIE.2017.086184","DOIUrl":"https://doi.org/10.1504/EJIE.2017.086184","url":null,"abstract":"Inventory management in today's complex manufacturing environments has become increasingly challenging. Ineffective management of inventory can lead to material shortages, excessive inventories, long lead times, waste of space, and poor customer service. Nowadays, various companies are using information systems to establish effective linkages to suppliers, customers, and other agents in the supply chain. These information systems include comprehensive data warehouses that integrate operational data within the supply chain including part usage, customer demand, defect rates, etc. The data can be used in analytics models to improve warehouse operations and inventory management. In this research, an approach is proposed for warehouse inventory management based on part clustering. The proposed approach categorises inventory parts based on their pick frequency, age, price, and sensitivity to transportation. Part grouping helps the decision makers to identify whether to keep the part in the warehouse, move it to an offsite inventory storage, or scrap it. The approach also determines when and how many parts should be moved from the offsite storage to the internal warehouse in order to balance the inventory and minimise the transportation costs. Dynamic reports are generated on a regular basis to effectively manage the inventory. [Received 3 September 2016; Revised 9 March 2017; Accepted 13 March 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.2017.086184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42807674","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 : 2017-08-31DOI: 10.1504/EJIE.2017.086186
A. Taleizadeh, Mohammad Sadegh Moshtagh, I. Moon
Over the last few decades, the closed loop supply chain (CLSC) has been examined because of concerns over the environment and social liability. In this paper, we propose a joint optimisation model of pricing strategies, quality levels, effort decisions, and return policies by considering the reference price effect in a three-level supply chain under different channel power structures. To investigate the impact of different scenarios on optimal decisions and performance of a CLSC, we address five different channel power structures: centralised, vertical Nash, manufacturer Stackelberg, retailer Stackelberg, and third party Stackelberg. We present a numerical example to demonstrate the theoretical results of the developed model, and we also compare the optimal decisions to determine the best channel power structures considered. Then, to examine the impact of the key parameters on the model's behaviour, we conduct a sensitivity analysis on the main parameters, and finally, we provide a conclusion. [Received 5 October 2016; Revised 9 March 2017; Accepted 24 March 2017]
{"title":"Optimal decisions of price, quality, effort level and return policy in a three-level closed-loop supply chain based on different game theory approaches","authors":"A. Taleizadeh, Mohammad Sadegh Moshtagh, I. Moon","doi":"10.1504/EJIE.2017.086186","DOIUrl":"https://doi.org/10.1504/EJIE.2017.086186","url":null,"abstract":"Over the last few decades, the closed loop supply chain (CLSC) has been examined because of concerns over the environment and social liability. In this paper, we propose a joint optimisation model of pricing strategies, quality levels, effort decisions, and return policies by considering the reference price effect in a three-level supply chain under different channel power structures. To investigate the impact of different scenarios on optimal decisions and performance of a CLSC, we address five different channel power structures: centralised, vertical Nash, manufacturer Stackelberg, retailer Stackelberg, and third party Stackelberg. We present a numerical example to demonstrate the theoretical results of the developed model, and we also compare the optimal decisions to determine the best channel power structures considered. Then, to examine the impact of the key parameters on the model's behaviour, we conduct a sensitivity analysis on the main parameters, and finally, we provide a conclusion. [Received 5 October 2016; Revised 9 March 2017; Accepted 24 March 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.2017.086186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44960202","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 : 2017-07-04DOI: 10.1504/EJIE.2017.084882
J. C. García-Díaz, Alexander D. Pulido-Rojano, V. Giner-Bosch
A multihead weighing process is a packaging technology that can be of strategic importance to a company, as it can be a key to competitive advantage in the modern food industry. The improvement in the process quality and sensory quality of food packaged in a multihead weighing process investigated in this paper is relevant to industrial engineering. A bi-objective ad hoc algorithm based on explicit enumeration for the packaging processes in multihead weighers with an unequal supply of the product to the weighing hoppers is developed. The algorithm uses an a priori strategy to generate Pareto-optimal solutions and select a subset of hoppers from the set of available ones in each packing operation. The relative importance of both aforementioned objectives is dynamically managed and adjusted. The numerical experiments are provided to illustrate the performance of the proposed algorithm and find the optimum operational conditions for the process. [Received 19 March 2016; Revised 8 November 2016; Revised 18 January 2017; Accepted 6 March 2017]
{"title":"Bi-objective optimisation of a multihead weighing process","authors":"J. C. García-Díaz, Alexander D. Pulido-Rojano, V. Giner-Bosch","doi":"10.1504/EJIE.2017.084882","DOIUrl":"https://doi.org/10.1504/EJIE.2017.084882","url":null,"abstract":"A multihead weighing process is a packaging technology that can be of strategic importance to a company, as it can be a key to competitive advantage in the modern food industry. The improvement in the process quality and sensory quality of food packaged in a multihead weighing process investigated in this paper is relevant to industrial engineering. A bi-objective ad hoc algorithm based on explicit enumeration for the packaging processes in multihead weighers with an unequal supply of the product to the weighing hoppers is developed. The algorithm uses an a priori strategy to generate Pareto-optimal solutions and select a subset of hoppers from the set of available ones in each packing operation. The relative importance of both aforementioned objectives is dynamically managed and adjusted. The numerical experiments are provided to illustrate the performance of the proposed algorithm and find the optimum operational conditions for the process. [Received 19 March 2016; Revised 8 November 2016; Revised 18 January 2017; Accepted 6 March 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.084882","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47297772","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 : 2017-07-04DOI: 10.1504/EJIE.2017.084880
J. M. Nilakantan, Zixiang Li, Qiuhua Tang, Peter Nielsen
Mixed-model assembly lines are becoming increasingly popular due to flexibility of producing customised products. In a mixed-model assembly line, line balancing and model sequencing problems are tightly interrelated and very important for efficiency. This paper proposes a new assembly line configuration based on paced mixed-model two-sided assembly lines where balancing and sequencing problems are considered simultaneously. Minimal work has been reported considering both problems simultaneously for this type of assembly line configuration. Two mixed-integer linear programming (MILP) models are developed and a restarted SA algorithm with new encoding, decoding and neighbourhood procedures is developed. The parameters of the proposed algorithm are selected based on a statistical technique and the performance of it is tested on a set of new benchmark problems. The computational results demonstrate the effectiveness of the MILP models and the high efficiency of the proposed algorithm. The proposed algorithm outperforms the comparative original SA algorithm. [Received 22 July 2016; Revised 1 December 2016; Accepted 14 February 2017]
{"title":"MILP models and metaheuristic for balancing and sequencing of mixed-model two-sided assembly lines","authors":"J. M. Nilakantan, Zixiang Li, Qiuhua Tang, Peter Nielsen","doi":"10.1504/EJIE.2017.084880","DOIUrl":"https://doi.org/10.1504/EJIE.2017.084880","url":null,"abstract":"Mixed-model assembly lines are becoming increasingly popular due to flexibility of producing customised products. In a mixed-model assembly line, line balancing and model sequencing problems are tightly interrelated and very important for efficiency. This paper proposes a new assembly line configuration based on paced mixed-model two-sided assembly lines where balancing and sequencing problems are considered simultaneously. Minimal work has been reported considering both problems simultaneously for this type of assembly line configuration. Two mixed-integer linear programming (MILP) models are developed and a restarted SA algorithm with new encoding, decoding and neighbourhood procedures is developed. The parameters of the proposed algorithm are selected based on a statistical technique and the performance of it is tested on a set of new benchmark problems. The computational results demonstrate the effectiveness of the MILP models and the high efficiency of the proposed algorithm. The proposed algorithm outperforms the comparative original SA algorithm. [Received 22 July 2016; Revised 1 December 2016; Accepted 14 February 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.084880","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43381627","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}
Supply chains in equipment-intensive service industries often involve repair operations. In this context, tactical inventory planning is concerned with optimally planning supplies and repairs based on demand forecasts and in the face of conflicting business objectives. This paper considers closed-loop supply chains and proposes a mixed-integer programming model and a metaheuristic approach to this problem. The model is open to a variety of network topologies, site functions and transfer policies. It also accommodates multiple objectives by the means of a weighted cost function. We report experiments on pseudo-random instances designed to evaluate plan quality and impact of cost weightings. In particular, we show how appropriate weightings allow to implement common planning strategies (e.g., just-in-time replenishment, minimal repair). [Received 8 May 2016; Revised 24 October 2016; Accepted 2 December 2016]
Pub Date : 2017-07-04DOI: 10.1504/EJIE.2017.084881
Chengfeng Wu, Qiuhong Zhao
In the paper, an uncooperative replenishment schedule with variable trade credit is considered under a supplier-Stackelberg game, which considers time-varying demand with time-varying price and learning curve production cost for the finite planning horizon in a two-echelon supply chain. We focus on discussing which condition induces the retailer and supplier both to accept the trade credit mechanism to increase own total profits. The main insights obtained are the following: 1) trade credit period coefficient only take two values 1 or 0; 2) the smaller the supplier's additional capital opportunity cost, the supplier is more willing to offer trade credit; 3) the greater the difference of the retailer's cost parameters and the supplier's cost parameters, the supplier is more likely to participate in the proposed strategy. The proposed model may be applied in some tech-products in the introduction and the growth phase or short-life-cycle and time-sensitive products, and so on. [Received 9 October 2014; Revised 13 April 2015; Revised 20 March 2016; Accepted 28 February 2017]
{"title":"An uncooperative ordering policy with time-varying price and learning curve for time-varying demand under trade credit","authors":"Chengfeng Wu, Qiuhong Zhao","doi":"10.1504/EJIE.2017.084881","DOIUrl":"https://doi.org/10.1504/EJIE.2017.084881","url":null,"abstract":"In the paper, an uncooperative replenishment schedule with variable trade credit is considered under a supplier-Stackelberg game, which considers time-varying demand with time-varying price and learning curve production cost for the finite planning horizon in a two-echelon supply chain. We focus on discussing which condition induces the retailer and supplier both to accept the trade credit mechanism to increase own total profits. The main insights obtained are the following: 1) trade credit period coefficient only take two values 1 or 0; 2) the smaller the supplier's additional capital opportunity cost, the supplier is more willing to offer trade credit; 3) the greater the difference of the retailer's cost parameters and the supplier's cost parameters, the supplier is more likely to participate in the proposed strategy. The proposed model may be applied in some tech-products in the introduction and the growth phase or short-life-cycle and time-sensitive products, and so on. [Received 9 October 2014; Revised 13 April 2015; Revised 20 March 2016; Accepted 28 February 2017]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.084881","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45317794","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 : 2017-07-04DOI: 10.1504/EJIE.2017.084877
Yushan Jiang, Bo Li, D. Song
This paper investigates a dual-channel supply chain consisting of a risk-neutral manufacturer and a risk-averse retailer. The manufacturer offers a consumer RP in the online channel, in which consumers face valuation uncertainty. We use conditional value-at-risk (CVaR) criterion to evaluate the risk-averse behaviour of the retailer. We examine how consumer RP and risk-averse behaviour influence the equilibrium solutions and supply chain agents' performance. It is shown that the manufacturer's optimal RP is related to consumer types. If the consumer has a moderate valuation of the product, the optimal RP depending on the retailer's risk-averse level. We observe a counter-intuitive phenomenon; the retailer's expected utility may increase under the double pressure of manufacturer encroachment and better returns service. Furthermore, a buyback revenue-sharing contract is offered to coordinate the dual-channel supply chain when the refund is endogenous. Finally, we explore several extensions. [Received 25 July 2015; Revised 27 October 2016; Accepted 13 November 2016]
{"title":"Analysing consumer RP in a dual-channel supply chain with a risk-averse retailer","authors":"Yushan Jiang, Bo Li, D. Song","doi":"10.1504/EJIE.2017.084877","DOIUrl":"https://doi.org/10.1504/EJIE.2017.084877","url":null,"abstract":"This paper investigates a dual-channel supply chain consisting of a risk-neutral manufacturer and a risk-averse retailer. The manufacturer offers a consumer RP in the online channel, in which consumers face valuation uncertainty. We use conditional value-at-risk (CVaR) criterion to evaluate the risk-averse behaviour of the retailer. We examine how consumer RP and risk-averse behaviour influence the equilibrium solutions and supply chain agents' performance. It is shown that the manufacturer's optimal RP is related to consumer types. If the consumer has a moderate valuation of the product, the optimal RP depending on the retailer's risk-averse level. We observe a counter-intuitive phenomenon; the retailer's expected utility may increase under the double pressure of manufacturer encroachment and better returns service. Furthermore, a buyback revenue-sharing contract is offered to coordinate the dual-channel supply chain when the refund is endogenous. Finally, we explore several extensions. [Received 25 July 2015; Revised 27 October 2016; Accepted 13 November 2016]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.084877","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66755881","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 : 2017-07-04DOI: 10.1504/EJIE.2017.084879
R. D. L. Torre, A. Lusa, M. Mateo
A mathematical model for optimising the strategic staff planning in universities is used to analyse the impact of different personnel and academic policies on the strategic staff plan, considering a preferable staff composition. The personnel policies are evaluated allowing or not the dismissals of permanent workers; the ratio of internal promotion for workers and the personnel budget. The academic policies are tested through the impact of different demand trends. Addressing the specificities of the university, the optimisation model considers not only economic criteria, i.e., personnel costs, but also other factors related to the fulfilment of the required service level and the achievement of a preferable workforce composition. Several computational scenarios are used, based on real data from the Universitat Politecnica de Catalunya (Barcelona, Spain). The results show the adjustment to the preferable workforce composition through the available mechanisms (dismissals, hiring and internal promotions). [Received 12 June 2015; Revised 24 November 2015; Revised 24 July 2016; Accepted 7 December 2016]
{"title":"Evaluation of the impact of strategic staff planning in a university using a MILP model","authors":"R. D. L. Torre, A. Lusa, M. Mateo","doi":"10.1504/EJIE.2017.084879","DOIUrl":"https://doi.org/10.1504/EJIE.2017.084879","url":null,"abstract":"A mathematical model for optimising the strategic staff planning in universities is used to analyse the impact of different personnel and academic policies on the strategic staff plan, considering a preferable staff composition. The personnel policies are evaluated allowing or not the dismissals of permanent workers; the ratio of internal promotion for workers and the personnel budget. The academic policies are tested through the impact of different demand trends. Addressing the specificities of the university, the optimisation model considers not only economic criteria, i.e., personnel costs, but also other factors related to the fulfilment of the required service level and the achievement of a preferable workforce composition. Several computational scenarios are used, based on real data from the Universitat Politecnica de Catalunya (Barcelona, Spain). The results show the adjustment to the preferable workforce composition through the available mechanisms (dismissals, hiring and internal promotions). [Received 12 June 2015; Revised 24 November 2015; Revised 24 July 2016; Accepted 7 December 2016]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.084879","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42789485","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 : 2017-03-24DOI: 10.1504/EJIE.2017.083248
O. Feyzioğlu, Nilay Noyan
We consider the toll pricing problem under uncertain network conditions resulting in stochastic travel times. Using the conditional value-at-risk (CVaR) as a risk measure on the alternate functions of the random travel times we introduce several travel time reliability-related network performance measures. CVaR is used to control the undesired realisations of random outcomes based on travel times, and consequently, improve the reliability of the transportation system. We characterise the random network parameters, which are in general highly correlated, by a set of scenarios and propose alternate risk-averse toll pricing models. These optimisation models involve decisions of transportation managers aiming to improve the system-wide network reliability and decisions of network users who are assumed to choose routes to minimise their expected total travel costs. We describe a solution method integrating mathematical programming approaches with a genetic algorithm. We also conduct a computational study to illustrate the effectiveness of the proposed approaches. [Received 26 December 2014; Revised 26 May 2016; Accepted 24 July 2016]
{"title":"Risk-averse toll pricing in a stochastic transportation network","authors":"O. Feyzioğlu, Nilay Noyan","doi":"10.1504/EJIE.2017.083248","DOIUrl":"https://doi.org/10.1504/EJIE.2017.083248","url":null,"abstract":"We consider the toll pricing problem under uncertain network conditions resulting in stochastic travel times. Using the conditional value-at-risk (CVaR) as a risk measure on the alternate functions of the random travel times we introduce several travel time reliability-related network performance measures. CVaR is used to control the undesired realisations of random outcomes based on travel times, and consequently, improve the reliability of the transportation system. We characterise the random network parameters, which are in general highly correlated, by a set of scenarios and propose alternate risk-averse toll pricing models. These optimisation models involve decisions of transportation managers aiming to improve the system-wide network reliability and decisions of network users who are assumed to choose routes to minimise their expected total travel costs. We describe a solution method integrating mathematical programming approaches with a genetic algorithm. We also conduct a computational study to illustrate the effectiveness of the proposed approaches. [Received 26 December 2014; Revised 26 May 2016; Accepted 24 July 2016]","PeriodicalId":51047,"journal":{"name":"European Journal of Industrial Engineering","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2017-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/EJIE.2017.083248","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44557219","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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