Modeling and heuristics for production time crashing in supply chain network design

Liao, Yi; Diabat, Ali; Alzaman, Chaher; Zhang, Yiqiang

doi:10.1007/s10479-020-03538-3

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…As shown in the figure, repair shops are enabled to extend their capacity, which produces an overall reduction in repair costs. The cost behavior follows the behavior of the crash cost in Liao et al [32] and Alzaman et al [3].…”

Section: A Scope Of Researchmentioning

confidence: 63%

“…This model integrates nonlinear functions that allow for greater flexibility in terms of output augmentation. At each shop facility, capacity can be extended using additional resources ( [3], [32]). By allowing for the extension of capacity, the repair lead time is reduced, and, specifically in the context of this study, the bike output per time period is increased.…”

Section: B Modelmentioning

confidence: 99%

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Predicting Bike Usage and Optimizing Operations at Repair Shops in Bike Sharing Systems

Alzaman

Aljuneidi

2023

IEEE Access

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Supply chain responsiveness and big data analytics (BDA) have garnered considerable interest in academia and among practitioners. BDA helps researchers understand the current challenges in data management, including the high volume, velocity, and variety of data. This study is concerned with improving the responsiveness of supply chain networks to bike-sharing systems (BSS), which exhibit BDA characteristics. To address the challenges of forecasting bike usage and accordingly optimizing repair shop operations, we analyze multi-factor BSS data (Data from Washington D.C. BSS available to public), wherein attributes, such as weather conditions, registration, humidity, date, and time, are present. We use machine learning algorithms, such as neural networks, decision-tree-based regression, K-nearest neighbor, support vectors, and ensemble random forest, to predict bike usage and repair. This work contests the results and demonstrates the effectiveness of combining machine learning with supply chain network design. Supply chain networks model bike repairs by means of capacity extensions, which entails a nonlinear problem. In this study, we utilize a gradient search to solve a nonlinear supply chain network model. By enabling capacity extension, bike repair shops within the BSS exhibit a promising 50 % reduction in lead repair time. Furthermore, a 25 % overall throughput increase in BSS is achieved. Ultimately, this study demonstrates the importance of operational flexibility in responding to big data challenges.INDEX TERMS Big data, bike sharing, flexibility, machine leaning, supply chain network design.

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Section: A Scope Of Researchmentioning

confidence: 63%

Section: B Modelmentioning

confidence: 99%

Predicting Bike Usage and Optimizing Operations at Repair Shops in Bike Sharing Systems

Alzaman

Aljuneidi

2023

IEEE Access

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“…As offering the BOPS service will impact retailer competition, it is worthwhile to investigate how BOPS may affect the competition of multiple retailers and their profits. ird, BOPS can be studied together with issues like manufacturer encroachment [46], supply chain design [47], and corporate social responsibility [48].…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

“Buy Online, Pick Up in Store” under Fit Uncertainty: To Offer or Not to Offer

2020

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Retailers offer BOPS (Buy Online, Pick Up in Store) service to improve consumers shopping experience. However, this greatly increases the decision complexity for retailers and consumers. For consumers, whether to purchase online or from a store with the BOPS service is a complex decision. This is especially true when the product has fit uncertainty. That is, consumers are uncertain about product fitness before using it. Also, their store visit cost can be heterogeneous and follows some distribution function. For a retailer, it needs to jointly optimize multiple decisions including the convenience degree of BOPS. To help the retailer develop the jointly optimal decisions, we first build a mathematical model where the retailer sells the product through online and store channel and analyzes the possible effects of BOPS. We find that the retailer should offer BOPS when the channel cost ratio (ratio of shipment fee divided by average store visit cost) is large enough. Through numerical studies, we show that the ratio of profit offering BOPS divided by the benchmark increases with the probability of product fit, shipment fee, and the convenience degree of BOPS. We then consider the case where the convenience degree of BOPS is also a decision itself. We find the optimal convenience degree of BOPS increases along with the average store visit cost and the probability of product fit. When the cost factor of offering the convenience for BOPS is larger than a threshold, the retailer should never offer BOPS.

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“…Second, actual data can be collected based on which our models and results can be tested empirically. Third, issues like network design, channel selection, and fulfillment service contracts can be addressed for dual-channel pharmaceutical supply chains [26,27].…”

mentioning

confidence: 99%

Coordination of a Dual-Channel Pharmaceutical Supply Chain Based on the Susceptible-Infected-Susceptible Epidemic Model

Hou

Wang

Chen

et al. 2020

IJERPH

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With the continuous development of Internet, online pharmaceutical channels in many countries have seen rapid expansion. As a result, pharmaceutical supply chain participants can adopt dual channels, namely, both online channels and offline channels. As online channels compete with traditional offline channels, it is of great relevance to study the potential conflicts and coordination between them, which is the focus of this paper. Specifically, this article develops a susceptible-infected-susceptible epidemic model of the dual channels for a pharmaceutical supply chain. Our main findings are that in a competitive situation, there is a positive stable equilibrium. Furthermore, increasing the rate of influence of offline transmission, online transmission, and cross transmission will improve sales. Moreover, improving the transmission influence rate will turn more potential customers into purchasers, increase channel sales, and achieve dual channel coordination. We then conduct numerical analysis to illustrate and complement the findings from the model. Finally, we provide managerial insights for implementing successful dual-channel pharmaceutical supply chains.

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Modeling and heuristics for production time crashing in supply chain network design

Cited by 7 publications

References 47 publications

Predicting Bike Usage and Optimizing Operations at Repair Shops in Bike Sharing Systems

Predicting Bike Usage and Optimizing Operations at Repair Shops in Bike Sharing Systems

“Buy Online, Pick Up in Store” under Fit Uncertainty: To Offer or Not to Offer

Coordination of a Dual-Channel Pharmaceutical Supply Chain Based on the Susceptible-Infected-Susceptible Epidemic Model

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