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[Objective] Due to the scarcity of helium resources, insufficient production, high external dependence and single source, the security situation of helium resources in China is very severe. Utilizing salt caverns for helium storage is a significantly advantageous technology for large-scale helium storage that can effectively guarantee the helium supply capacity and improve helium security. However,China is devoid of underground salt cavern helium storage in operation, and related research and construction are still in the stage of initial development, requiring targeted feasibility and key technology researches. [Methods] Based on an investigation of helium resources and helium storage construction as well as China's experience in salt cavern gas storage construction, the feasibility of salt cavern helium storage construction in China was analyzed, and the suggestions on the development of key technologies for salt cavern helium storage were proposed,such as site evaluation, airtightness evaluation, cavern construction, storage construction, and helium injection and extraction. [Results] China is facing a high risk of helium supply disruption, necessitating the enlargement of reserve capacity. Salt cavern is suitable for large-scale helium storage for its satisfying performance in security and airtightness. The construction of salt cavern helium storage is feasible to increase China's helium reserve, giving that China has abundant salt cavern resources and a technological base for cavern construction. In addition, it is necessary to perform targeted research on key technologies for salt cavern helium storage construction, considering the geological conditions and helium resource conditions for storage construction in China differ from those in foreign countries. The salt mine in the southeast coastal area is close to the import and consumption of helium, and the transportation cost is low, so it can be used as the preferred storage site for the construction of salt cavern helium storage in China. [Conclusion] It is recommended to construct salt cavern helium storage in China in stages.At the early stage, 1 to 2 helium storage caverns should be constructed to explore and verify the construction technology of helium storage and ensure a stable supply of helium in China, after that more caverns should be constructed gradually to build up a strategic reserve that can meet China's helium demand for 5 to 10 years.

Low temperature waste-heat heating is an important technology for clean heating.But the resource potential of low temperature waste-heat used for heating will be affected by time, space, temperature, industrial development and other factors.Therefore, the resource potential of low temperature waste-heat for long-term, effective & stable heating should be studied.In this study, the resource potential of low temperature waste-heat for heating was studied by the scenario analysis method and the results show that, the low temperature waste-heat resources available for heating in the northern region are about 62.262 million tce, and the heating area is about 8.12 billion square meters in 2017.Among them, the low temperature waste-heat resources above 80℃ account for 25.2%.In the future, the low temperature waste-heat resources available for heating will be 68.98 million tce, and the heating area is about 12.14 billion square meters in 2020.The low temperature waste-heat resources available for heating will be 66.487 million tce, and the heating area is about 11.7 billion square meters in 2030.

Problem definition: We study open-shop service networks where customers go through multiple services. We were motivated by a partnering health screening clinic, where customers are routed by a dispatcher and operational performance is measured at two levels: micro-level, via waits for individual services, and macro-level, via overall wait. Both measures reflect customer experience and could support its management. Our analysis revealed that waits were long and increased along the service process. Such long waits give rise to negative waiting experience and the increasing shape is detrimental as it is known to create perceived waits that are even longer. Our goal is hence to analyze strategies that shape and improve customers' perceived experience. Methodology/results: Analytically, we use a stylized two-station open-shop network to show that prioritizing advanced customers, jointly with pooling (virtual) queues, can improve both macro- and micro-level performance. We validate these findings with a simulation model, calibrated with our clinic's data. Practically, we find that an automated routing system (ARS), recently implemented in the clinic, had a negligible impact on overall wait—It simply redistributed waiting among wait-for-routing and wait-for-service. However, ARS renders applicable sophisticated priority and routing policies (that were infeasible under the manual routing practice), specifically the ones arising from the present research. Managerial implications: Our study amplifies performance benefits of accounting for individual customers' system status in addition to station-level load information. We offer insights into the implementation of new technologies: Firms better plan for fundamental changes in their operation rather than harness new technology to their existing operation, which may be suboptimal due to past technical limitations. History: This paper has been accepted in the Manufacturing & Service Operations Management Frontiers in Operations Initiative. Funding: M. Chen acknowledges the support from the National Natural Science Foundation of China [Grant 72301280]. O. Baron acknowledges the support from the Natural Science and Engineering Research Council of Canada. J. Wang acknowledges the support from the City University of Hong Kong [Grant 11505421]. A. Mandelbaum is partially supported by the Israel Science Foundation [Grant 491/22]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.0590. [ABSTRACT FROM AUTHOR]

This paper examines different car-sharing models offered by ride-hailing firms. In the traditional model, customers are served individually. In the sharing-only model, all customers are willing to share the ride with other customers. In the hybrid model, customers may choose either individual or shared service provided by the same fleet. Sharing customers incur a hassle cost. We develop a queueing game-theoretic model to (i) determine the arrival rates that maximizes social welfare and (ii) choose admission fees that maximizes firm profits. First, we discover a tipping point in the hybrid model. When hassle cost decreases to this point, (i) the optimal customer behavior immediately switches from less than 80% sharing customers to 100%, (ii) the optimal arrival rate increases dramatically, and (iii) the rate at which a decreasing hassle cost improves the maximum social welfare significantly increases. Second, when hassle cost is higher than the tipping point, the hybrid model may generate higher social welfare than the other two models. Hence, the firm can improve social welfare by assigning customers to differentiated services even when they are not heterogeneous. Finally, we propose a profit-maximizing admission fee structure in the hybrid model to maximize firm profits and demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

This paper, motivated by a collaboration with a healthcare service provider, focuses on stochastic open-shop service networks with two objectives: more traditional macrolevel measures (such as minimizing total system time or minimizing total number of tardy customers) and the atypical microlevel measure of reducing the incidents of excessively long waits at any workstation within the process. While work-conserving policies are optimal for macrolevel measures, scheduling policies with strategic idleness (SI) might be helpful for microlevel measures. Using the empirical data obtained from the service provider, we provide statistical evidence that SI is used by its schedulers to manage the macro- and microlevel measures. However, the company has no specific rules on implementing SI and the schedulers make decisions based on their own experience. Our primary goal is to develop a systematic framework for the joint usage of SI with dynamic scheduling policies (DSPs). We suggest to use threshold-based policies to intelligently combine SI and DSPs and show that the resulting policies provide an efficient way to simultaneously address both macro- and microlevel measures. We build two simulation models: one based on empirical data and one based on a randomly generated open-shop network. We use both models to demonstrate that an open-shop service network can be systematically and effectively managed to deliver improved service level by using SI. Funding: The first three authors acknowledge financial support from their respective Natural Sciences and Engineering Research Council of Canada grants. Supplemental Material: The online appendix is abailable at https://doi.org/10.1287/msom.2016.0591. Keywords: strategic idleness * dynamic scheduling policy * open shop * healthcare * service network, 1. Introduction In this paper, we focus on stochastic open-shop processes operating under multiple objectives. The system objectives include a combination of the more traditional macrolevel measures (such as minimizing [...]