This paper is motivated by the rapid development of community group buying (CGB), where the CGB platform dramatically relies on the community leader to provide last-mile services and fulfill consumers’ orders. Considering two types of community leaders, the friend role and seller role, this work adopts a game-theoretical model and investigates how the pricing strategy, uniform pricing strategy (N) or differentiated pricing strategy (Y), affects players’ performance and decisions on effort level. This study shows that the commission rate is an essential factor in stimulating the role transformation of community leaders. A significantly large commission rate results in the friend role community leader with lower trust value changing into the seller role. Generally, the community leader works harder under the uniform pricing scenario except in situations with a significant commission rate and moderate sensitivity coefficient of trust value. However, the effort level of the platform is jointly influenced by the pricing strategy, commission rate, and the role of a community leader. Moreover, regardless of the commission rate, when the community leader is a friend role and the trust value is high, both the platform and community leader can gain higher profits under the uniform pricing scenario than the differentiated pricing case. It indicates that a win-win situation can be achieved.
{"title":"Pricing strategy and its impact on the effort of community leader and platform: uniform or differentiated pricing?","authors":"Bin Liu, Bingchun Li, Juan Li, Qiaoyun Yun","doi":"10.1051/ro/2024146","DOIUrl":"https://doi.org/10.1051/ro/2024146","url":null,"abstract":"This paper is motivated by the rapid development of community group buying (CGB), where the CGB platform dramatically relies on the community leader to provide last-mile services and fulfill consumers’ orders. Considering two types of community leaders, the friend role and seller role, this work adopts a game-theoretical model and investigates how the pricing strategy, uniform pricing strategy (N) or differentiated pricing strategy (Y), affects players’ performance and decisions on effort level. This study shows that the commission rate is an essential factor in stimulating the role transformation of community leaders. A significantly large commission rate results in the friend role community leader with lower trust value changing into the seller role. Generally, the community leader works harder under the uniform pricing scenario except in situations with a significant commission rate and moderate sensitivity coefficient of trust value. However, the effort level of the platform is jointly influenced by the pricing strategy, commission rate, and the role of a community leader. Moreover, regardless of the commission rate, when the community leader is a friend role and the trust value is high, both the platform and community leader can gain higher profits under the uniform pricing scenario than the differentiated pricing case. It indicates that a win-win situation can be achieved.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":" 41","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831409","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}
Blockchain technology has reshaped how members of supply chains transfer information, effectively avoiding the phenomenon of information silos and helping to improve the emissions reduction performance and profit of each subject in the supply chain. It is now critical to understand how supply chain members can be encouraged to collaboratively invest in low-carbon service platforms based on blockchain technology to realise chain-wide systematic carbon reduction. In this regard, considering the time-dynamic characteristics of enterprise emissions reduction, this paper establishes a differential game model of collaborative emissions reduction in a low-carbon supply chain composed of a Stackelberg leader manufacturer and a supplier. We compare and analyse the four investment decision scenarios regarding whether the supplier and manufacturer invest in the blockchain low-carbon service platform under decentralised decision-making, as well as the equilibrium solutions of supply chain members under centralised decision-making scenarios by solving the Hamilton function. Finally, we introduce a bilateral cost-sharing contract to make the supply chain perfectly coordinated. We find that the significant unit return is an important incentive for supply chain members to take the lead in investing in a low carbon service platform (LCSP). In this regard, when only one member invests, the other one demonstrates free-riding behaviour. Under centralised decision-making, the supply chain can achieve Pareto optimality, and the bilateral cost-sharing contract can achieve perfect coordination of the supply chain, which is the best choice for the decision-makers of low-carbon supply chains. As the influence level of the LCSP gradually increases from small to large, the optimal decision-making of supply chain members gradually transitions from waiting for the right time to ‘hitchhike’ to a strong willingness to cooperate. This study is of great reference value and practical significance for economic entities to improve profits, promote systematic carbon reduction in the whole chain and promote the sustainable development of low-carbon supply chains.
{"title":"Decision-making in low carbon supply chains: A blockchain-based LCSP perspective and a differential game model","authors":"Yingying Xu, Zhenni Zhang","doi":"10.1051/ro/2024145","DOIUrl":"https://doi.org/10.1051/ro/2024145","url":null,"abstract":"Blockchain technology has reshaped how members of supply chains transfer information, effectively avoiding the phenomenon of information silos and helping to improve the emissions reduction performance and profit of each subject in the supply chain. It is now critical to understand how supply chain members can be encouraged to collaboratively invest in low-carbon service platforms based on blockchain technology to realise chain-wide systematic carbon reduction. In this regard, considering the time-dynamic characteristics of enterprise emissions reduction, this paper establishes a differential game model of collaborative emissions reduction in a low-carbon supply chain composed of a Stackelberg leader manufacturer and a supplier. We compare and analyse the four investment decision scenarios regarding whether the supplier and manufacturer invest in the blockchain low-carbon service platform under decentralised decision-making, as well as the equilibrium solutions of supply chain members under centralised decision-making scenarios by solving the Hamilton function. Finally, we introduce a bilateral cost-sharing contract to make the supply chain perfectly coordinated. We find that the significant unit return is an important incentive for supply chain members to take the lead in investing in a low carbon service platform (LCSP). In this regard, when only one member invests, the other one demonstrates free-riding behaviour. Under centralised decision-making, the supply chain can achieve Pareto optimality, and the bilateral cost-sharing contract can achieve perfect coordination of the supply chain, which is the best choice for the decision-makers of low-carbon supply chains. As the influence level of the LCSP gradually increases from small to large, the optimal decision-making of supply chain members gradually transitions from waiting for the right time to ‘hitchhike’ to a strong willingness to cooperate. This study is of great reference value and practical significance for economic entities to improve profits, promote systematic carbon reduction in the whole chain and promote the sustainable development of low-carbon supply chains.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"32 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141649195","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}
This research examines the operation decisions of the online supply chain for heterogeneous products under different financing modes: e-commerce platform financing or bank financing, when manufacturers face funding constraints. Considering the manufacturer's adoption of differentiated channel strategies when providing heterogeneous products is also considered, and combined with the impact of online reviews on consumer utility, an e-commerce platform online dual-channel financing model is constructed. The research findings are as follows: (i) when the effectiveness of online reviews differs within a certain range, the equilibrium solution exists. If the relative interest rates of the e-commerce platforms and bank change within a certain range, the same financing mode can bring mutual benefits to both the manufacturer and e-commerce platform, resulting in a "win-win" situation. (ii) If the interest rates under both financing modes are the same, the e-commerce platform financing mode has a higher wholesale price, but the difference in retail prices of distribution products depends on the costs difference between the two products, and at this point, the manufacturer will select e-commerce platform financing mode. (iii) At the optimal interest rate, when the cost of heterogenous products is the same, the e-commerce platform consistently offers a more favorable interest rate compared to the bank's optimal rate. when the e-commerce platform’s commission and the positive difference in product reviews is large, the manufacturer will choose e-commerce platform financing mode. Under the e-commerce platform financing mode, both the manufacturer and e-commerce platform are willing to provide lower retail prices to attract more consumers.
{"title":"Heterogeneous products operation decisions of online dual-channel supply chain considering online reviews under different financing modes","authors":"Pingping Shi, Jiamin Wang, Yaogang Hu, Huaping Yin, Zhengmao Chen, Biao Xu, Yue Duan","doi":"10.1051/ro/2024144","DOIUrl":"https://doi.org/10.1051/ro/2024144","url":null,"abstract":"This research examines the operation decisions of the online supply chain for heterogeneous products under different financing modes: e-commerce platform financing or bank financing, when manufacturers face funding constraints. Considering the manufacturer's adoption of differentiated channel strategies when providing heterogeneous products is also considered, and combined with the impact of online reviews on consumer utility, an e-commerce platform online dual-channel financing model is constructed. The research findings are as follows: (i) when the effectiveness of online reviews differs within a certain range, the equilibrium solution exists. If the relative interest rates of the e-commerce platforms and bank change within a certain range, the same financing mode can bring mutual benefits to both the manufacturer and e-commerce platform, resulting in a \"win-win\" situation. (ii) If the interest rates under both financing modes are the same, the e-commerce platform financing mode has a higher wholesale price, but the difference in retail prices of distribution products depends on the costs difference between the two products, and at this point, the manufacturer will select e-commerce platform financing mode. (iii) At the optimal interest rate, when the cost of heterogenous products is the same, the e-commerce platform consistently offers a more favorable interest rate compared to the bank's optimal rate. when the e-commerce platform’s commission and the positive difference in product reviews is large, the manufacturer will choose e-commerce platform financing mode. Under the e-commerce platform financing mode, both the manufacturer and e-commerce platform are willing to provide lower retail prices to attract more consumers.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"5 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141652329","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}
Growing businesses are concerned with doing well both environmentally and economically. Pointing out this view, this paper explores the game theoretical approach (Stackelberg and Bertrand) for a two-echelon green supply chain where the duopolistic manufacturers produce two substitutable green products and sell their products through a common retailer. The demands for both green products are functions of the selling prices and green levels (GLs). The effects of power structures on optimal price and green level decisions and associated equilibrium decisions are examined in three scenarios. Firstly, trilateral competition manufacturer-led Stackelberg (MS); secondly, retailer-led Stackelberg (RS); and thirdly, vertical collaboration, and compares the optimal decisions analytically. Our investigations show that, in addition to increasing the product's greening level, vertical collaboration creates a win-win situation for collaboration members, whereas the manufacturer outside the collaboration experiences a decline in profits. Additionally, we find that the overall profit from vertical collaboration is greater than the sum of the individual profits corresponding to two participants in the trilateral competition models (MS and RS). Further, a selection criterion is developed for retailer to select the most suitable manufacturer for vertical collaboration. Finally, a numerical example and a sensitivity analysis are performed to determine the impact of parameters.
{"title":"Pricing and green quality decisions in two-stage green supply chain for substitutable green products: a game-theoretic approach","authors":"Shivendra Kumar Gupta, Vinod Kumar Mishra","doi":"10.1051/ro/2024143","DOIUrl":"https://doi.org/10.1051/ro/2024143","url":null,"abstract":"Growing businesses are concerned with doing well both environmentally and economically. Pointing out this view, this paper explores the game theoretical approach (Stackelberg and Bertrand) for a two-echelon green supply chain where the duopolistic manufacturers produce two substitutable green products and sell their products through a common retailer. The demands for both green products are functions of the selling prices and green levels (GLs). The effects of power structures on optimal price and green level decisions and associated equilibrium decisions are examined in three scenarios. Firstly, trilateral competition manufacturer-led Stackelberg (MS); secondly, retailer-led Stackelberg (RS); and thirdly, vertical collaboration, and compares the optimal decisions analytically. Our investigations show that, in addition to increasing the product's greening level, vertical collaboration creates a win-win situation for collaboration members, whereas the manufacturer outside the collaboration experiences a decline in profits. Additionally, we find that the overall profit from vertical collaboration is greater than the sum of the individual profits corresponding to two participants in the trilateral competition models (MS and RS). Further, a selection criterion is developed for retailer to select the most suitable manufacturer for vertical collaboration. Finally, a numerical example and a sensitivity analysis are performed to determine the impact of parameters.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"57 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141652683","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}
In recent years, the government has issued regulations on environmental protection, carbon emissions, and trading. Enterprises' environmental awareness has increased, and the operational strategies of manufacturers and platforms have also been affected by environmental regulations. This study considers the interactive effects of agency and reselling contracts between manufacturers and platforms and the cap-and-trade regulation on return policy. Our findings reveal that government-imposed caps on total carbon emissions consistently influence optimal pricing and profits under cap-and-trade regulation, regardless of the presence of a return policy. Additionally, the emission intensity of manufacturers plays a pivotal role in determining the return policy. High manufacturer emission intensity leads decision-makers to provide return services only under specific conditions. Moreover, manufacturers opt for agency contracts when faced with low commission rates, and this threshold is intricately linked to carbon emission intensity, the cap, and the return rate. The government's ability to adjust the cap enables control over changes in manufacturers' profits and output, thereby influencing industrial structure and carbon emissions. Manufacturers strategically choose return policies, considering factors such as carbon intensity, return rate, and commission rate. Remarkably, even under cap-and-trade regulations, manufacturers remain inclined to offer returns under optimal conditions.
{"title":"Agency or reselling: Optimal return policy in e-commerce retail systems under cap-and-trade regulation","authors":"Jie Wu, Wei Wang, Mingjun Li, Xiang Ji","doi":"10.1051/ro/2024139","DOIUrl":"https://doi.org/10.1051/ro/2024139","url":null,"abstract":"In recent years, the government has issued regulations on environmental protection, carbon emissions, and trading. Enterprises' environmental awareness has increased, and the operational strategies of manufacturers and platforms have also been affected by environmental regulations. This study considers the interactive effects of agency and reselling contracts between manufacturers and platforms and the cap-and-trade regulation on return policy. Our findings reveal that government-imposed caps on total carbon emissions consistently influence optimal pricing and profits under cap-and-trade regulation, regardless of the presence of a return policy. Additionally, the emission intensity of manufacturers plays a pivotal role in determining the return policy. High manufacturer emission intensity leads decision-makers to provide return services only under specific conditions. Moreover, manufacturers opt for agency contracts when faced with low commission rates, and this threshold is intricately linked to carbon emission intensity, the cap, and the return rate. The government's ability to adjust the cap enables control over changes in manufacturers' profits and output, thereby influencing industrial structure and carbon emissions. Manufacturers strategically choose return policies, considering factors such as carbon intensity, return rate, and commission rate. Remarkably, even under cap-and-trade regulations, manufacturers remain inclined to offer returns under optimal conditions.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"98 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141835218","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}
This paper delves into the axial Three-index Assignment Problem (3IAP), alternatively known as the Multi-dimensional Assignment Problem, defined as an extension of the classical two-dimensional assignment problem. The 3IAP entails allocating $n$ tasks to $n$ machines in $n$ factories, ensuring one task is completed by one machine in one factory at a minimum total cost. This combinatorial optimization problem is classified as emph{NP}-hard due to its inherent complexity and being the subject of much scholarly research and investigation. The study employs an algorithmic approach to devise rapid and effective solutions for the 3IAP. A new heuristic Greedy-style Procedure (GSP) is introduced for solving the 3IAP, achieving feasible solutions within polynomial time. Particular configurations of cost matrices enable us to reach quality solutions. Examining tie-cases and matrix ordering unveiled innovative variants. Further investigation of cost matrix attributes facilitates the development of two new heuristic categories, offering optimal or nearly optimal solutions for the 3IAP. Extensive numerical experiments validate the effectiveness of the heuristics, generating quality solutions in a short computational time. Furthermore, we implement two potent methods using optimization solvers, achieving optimal solutions for the 3IAP within competitive CPU times.
{"title":"Solution approaches to the three-index assignment problem","authors":"Mohamed Mehbali","doi":"10.1051/ro/2024140","DOIUrl":"https://doi.org/10.1051/ro/2024140","url":null,"abstract":"This paper delves into the axial Three-index Assignment Problem (3IAP), alternatively known as the Multi-dimensional Assignment Problem, defined as an extension of the classical two-dimensional assignment problem. The 3IAP entails allocating $n$ tasks to $n$ machines in $n$ factories, ensuring one task is completed by one machine in one factory at a minimum total cost. This combinatorial optimization problem is classified as emph{NP}-hard due to its inherent complexity and being the subject of much scholarly research and investigation. \u0000The study employs an algorithmic approach to devise rapid and effective solutions for the 3IAP. A new heuristic Greedy-style Procedure (GSP) is introduced for solving the 3IAP, achieving feasible solutions within polynomial time. Particular configurations of cost matrices enable us to reach quality solutions. Examining tie-cases and matrix ordering unveiled innovative variants. Further investigation of cost matrix attributes facilitates the development of two new heuristic categories, offering optimal or nearly optimal solutions for the 3IAP.\u0000Extensive numerical experiments validate the effectiveness of the heuristics, generating quality solutions in a short computational time. Furthermore, we implement two potent methods using optimization solvers, achieving optimal solutions for the 3IAP within competitive CPU times.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"2 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655813","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}
This research examines the application of the Theory of Swift, Even Flow (TSEF) by a distribution company to improve the performance of its processes for parcels. TSEF was deployed by the company after experiencing lean improvement fatigue and diminishing returns from the time and effort invested. This case study combined quantitative and qualitative approaches to develop a good understanding of the operation. This approach enabled the business to utilise Discrete Event Simulation (DES), which facilitated the implementation of TSEF. From this study, the development of a novel DES application revealed the primacy of process variation and throughput time, key factors in TSEF, in driving improvements. The derived DES approach is reproducible and demonstrates its utility with production improvement frameworks. TSEF, through the visualisations and analysis provided by DES, broadened the scope of improvements to an enterprise level, therefore assisting the business managers in driving forward when lean improvement techniques stagnated. The impact of the research is not limited to the theoretical contribution, as the combination of DES and TSEF led to significant managerial insights on how to overcome obstacles and substantiate change.
本研究探讨了一家配送公司如何应用 "快速均匀流理论"（TSEF）来提高包裹流程的绩效。该公司在经历了精益改进疲劳和投入的时间和精力收益递减之后，采用了 TSEF。本案例研究结合了定量和定性方法，以充分了解公司的运营情况。这种方法使企业能够利用离散事件模拟 (DES)，从而促进 TSEF 的实施。通过这项研究，新型 DES 应用程序的开发揭示了流程变化和吞吐时间（TSEF 的关键因素）在推动改进方面的重要性。衍生的 DES 方法具有可重复性，并证明了其在生产改进框架中的实用性。通过 DES 提供的可视化和分析，TSEF 将改进范围扩大到了企业层面，从而在精益改进技术停滞不前时，帮助企业管理者向前推进。这项研究的影响不仅限于理论贡献，因为 DES 和 TSEF 的结合为如何克服障碍和实现变革提供了重要的管理见解。
{"title":"Smoothly pass the parcel: implementing the theory of swift, even flow","authors":"W. Garn, James Aitken, R. Schmenner","doi":"10.1051/ro/2024142","DOIUrl":"https://doi.org/10.1051/ro/2024142","url":null,"abstract":"This research examines the application of the Theory of Swift, Even Flow (TSEF) by a distribution company to improve the performance of its processes for parcels. TSEF was deployed by the company after experiencing lean improvement fatigue and diminishing returns from the time and effort invested. This case study combined quantitative and qualitative approaches to develop a good understanding of the operation. This approach enabled the business to utilise Discrete Event Simulation (DES), which facilitated the implementation of TSEF. From this study, the development of a novel DES application revealed the primacy of process variation and throughput time, key factors in TSEF, in driving improvements. The derived DES approach is reproducible and demonstrates its utility with production improvement frameworks. TSEF, through the visualisations and analysis provided by DES, broadened the scope of improvements to an enterprise level, therefore assisting the business managers in driving forward when lean improvement techniques stagnated. The impact of the research is not limited to the theoretical contribution, as the combination of DES and TSEF led to significant managerial insights on how to overcome obstacles and substantiate change.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"104 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657548","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}
Product distribution in supply chain management has been hotly debated during the last decade. However, during COVID-19, many supply chains suffered from sudden changes in local market demands. Such changes cause a bullwhip effect throughout a supply chain, making them unable to respond rapidly. This research develops a new model for distributing products in the food chain using real urban and geographical data of blockchain technology. The aim is to re-adjust the product distribution plans by using a horizontal layer product distribution readjustment strategy while local markets confront sudden market changes. To address the problem, a heuristic was proposed and coded by Python based on the largest density-distance rule. Then, to evaluate the performance of the proposed method, the schedules are assessed with some metrics gathered in the literature. For this purpose, a Full Factorial design of experiments is generated by Python. Moreover, the outcomes are compared with those gained from short-traveling time and greedy loading-based heuristics. The results showed that using the horizontal layer product distribution readjustment strategy for modifying the initial schedules could prevent lost sales in all studied cases. Besides, by responding to sudden market demand changes rapidly, which subsequently causes preventing lost sales, more profits were gained in 58.3% of the studied cases. In addition, in 61.11% of studied cases, the proposed method was faster than other studied heuristics in terms of computational time.
{"title":"Blockchain technology and mitigating bullwhip effect in supply chains with uncertain markets: a horizontal layer product distribution strategy","authors":"Aidin Delgoshaei, Mohd Khairol Anuar Ariffin","doi":"10.1051/ro/2024141","DOIUrl":"https://doi.org/10.1051/ro/2024141","url":null,"abstract":"Product distribution in supply chain management has been hotly debated during the last decade. However, during COVID-19, many supply chains suffered from sudden changes in local market demands. Such changes cause a bullwhip effect throughout a supply chain, making them unable to respond rapidly. This research develops a new model for distributing products in the food chain using real urban and geographical data of blockchain technology. The aim is to re-adjust the product distribution plans by using a horizontal layer product distribution readjustment strategy while local markets confront sudden market changes. To address the problem, a heuristic was proposed and coded by Python based on the largest density-distance rule. Then, to evaluate the performance of the proposed method, the schedules are assessed with some metrics gathered in the literature. For this purpose, a Full Factorial design of experiments is generated by Python. Moreover, the outcomes are compared with those gained from short-traveling time and greedy loading-based heuristics. The results showed that using the horizontal layer product distribution readjustment strategy for modifying the initial schedules could prevent lost sales in all studied cases. Besides, by responding to sudden market demand changes rapidly, which subsequently causes preventing lost sales, more profits were gained in 58.3% of the studied cases. In addition, in 61.11% of studied cases, the proposed method was faster than other studied heuristics in terms of computational time.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"101 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657590","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}
In work of Roman A. Polyak [3], the Modified Chen-Harker- Kanzow-Smale (CHKS) function was studied to relate a multiplier method and a Interior Prox method with the second order distance function. Independently, the dislocated hyperbolic penalty function (DHPF) was proposed by A.E. Xavier (1992). DHPF was rewritten and studied in [1] and [2]. Thus, this function was called the dislocated hyperbolic function (DHF). In this work, we note that DHF is a particular case of CHKS function. Then we will call the DHF function as the dislocation hyperbolic transformation function.
Roman A. Polyak [3]研究了修正的 Chen-Harker-Kanzow-Smale (CHKS) 函数，将乘法和内部 Prox 法与二阶距离函数联系起来。另外，A.E. Xavier（1992 年）提出了错位双曲惩罚函数（DHPF）。文献[1]和[2]对 DHPF 进行了改写和研究。因此，该函数被称为位错双曲函数（DHF）。在本文中，我们注意到 DHF 是 CHKS 函数的特殊情况。因此，我们将 DHF 函数称为位错双曲变换函数。
{"title":"A note on the dislocation hyperbolic transformation function","authors":"Lennin Mallma Ramirez, N. Maculan","doi":"10.1051/ro/2024134","DOIUrl":"https://doi.org/10.1051/ro/2024134","url":null,"abstract":"In work of Roman A. Polyak [3], the Modified Chen-Harker-\u0000Kanzow-Smale (CHKS) function was studied to relate a multiplier\u0000method and a Interior Prox method with the second order distance\u0000function. Independently, the dislocated hyperbolic penalty function\u0000(DHPF) was proposed by A.E. Xavier (1992). DHPF was rewritten\u0000and studied in [1] and [2]. Thus, this function was called the dislocated\u0000hyperbolic function (DHF). In this work, we note that DHF is a\u0000particular case of CHKS function. Then we will call the DHF function\u0000as the dislocation hyperbolic transformation function.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"24 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685120","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}
This paper focuses on linear programming problems in a rough interval environment. By introducing four linear programming problems, an attempt is being made to propose some results on optimal value of a linear programming problem with rough interval parameters. To obtain optimal solutions of a linear programming problem with rough interval data, constraints of the four proposed linear problems are applied. Furthermore, two solution concepts, surely and possibly solutions, are defined. Some numerical examples demonstrate the validity of the results. In particular, a scheduling problem and a fixed-charge transportation problem (FCTP) under rough interval uncertainty are investigated.
{"title":"Some new results on rough interval linear programming problems and their application to scheduling and fixed-charge transportation problems","authors":"Mehdi Allahdadi, Sanaz Rivaz","doi":"10.1051/ro/2024137","DOIUrl":"https://doi.org/10.1051/ro/2024137","url":null,"abstract":"This paper focuses on linear programming problems in a rough interval environment. By introducing four linear programming problems, an attempt is being made to propose some results on optimal value of a linear programming problem with rough interval parameters. To obtain optimal solutions of a linear programming problem with rough interval data, constraints of the four proposed linear problems are applied. Furthermore, two solution concepts, surely and possibly solutions, are defined. Some numerical examples demonstrate the validity of the results. In particular, a scheduling problem and a fixed-charge transportation problem (FCTP) under rough interval uncertainty are investigated.","PeriodicalId":506995,"journal":{"name":"RAIRO - Operations Research","volume":"53 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141688450","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：