Regret-Minimizing Project Choice

An agent observes the set of available projects and proposes some, but not necessarily all, of them. A principal chooses one or none from the proposed set. We solve for a mechanism that minimizes the principal's worst-case regret. We compare the single-project environment in which the agent can propose only one project with the multiproject environment in which he can propose many. In both environments, if the agent proposes one project, it is chosen for sure if the principal's payoff is sufficiently high; otherwise, the probability that it is chosen decreases in the agent's payoff. In the multiproject environment, the agent's payoff from proposing multiple projects equals his maximal payoff from proposing each project alone. The multiproject environment outperforms the single-project one by providing better fallback options than rejection and by delivering this payoff to the agent more efficiently

Dynamic Mechanisms without Money

We analyze the optimal design of dynamic mechanisms in the absence of transfers. The designer uses future allocation decisions as a way of eliciting private information. Values evolve according to a two-state Markov chain. We solve for the optimal allocation rule, which admits a simple implementation. Unlike with transfers, efficiency decreases over time, and both immiseration and its polar opposite are possible long-run outcomes. Considering the limiting environment in which time is continuous, we show that persistence hurts

Dynamic Allocation without Money

We analyze the optimal design of dynamic mechanisms in the absence of transfers. The agent’s value evolves according to a two-state Markov chain. The designer uses future allocation decisions to elicit private information. We solve for the optimal allocation mechanism. Unlike with transfers, efficiency decreases over time. In the long run, polarization occurs. A simple implementation is provided. The agent is endowed with a “quantified entitlement,” corresponding to the number of units he is entitled to claim in a row

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP) is proposed. Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints), the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency. Findings: In the process of the subproblems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality. Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop. Originality/value: The research provides an efficient scheduling method for the large-scale job shops, and will be helpful for the discrete manufacturing industry for improving the production efficiency and effectiveness.Peer Reviewe

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP) is proposed. Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints), the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency. Findings: In the process of the subproblems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality. Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop. Originality/value: The research provides an efficient scheduling method for the large-scale job shops, and will be helpful for the discrete manufacturing industry for improving the production efficiency and effectiveness.Peer Reviewe

Identifying barriers to the care of the rheumatoid hand in China: comparing attitudes of rheumatologists and hand surgeons

AimIn China, hand surgeons treat fewer rheumatoid arthritis (RA) patients compared to other countries. We investigated whether physician and surgeon knowledge, attitudes and practices regarding RA hand deformities reflect current evidence and may contribute to the low utilization of surgery.MethodWe surveyed hand surgeons and rheumatologists at three tertiary hospitals in Beijing, China. Questionnaires were developed from literature and expert review to assess their knowledge, attitudes and practice patterns related to rheumatoid hand surgery.ResultsThirtyâ five hand surgeons and 59 rheumatologists completed the survey. Roughly oneâ third felt that the rheumatologists and hand surgeons agree on how to manage RA hand deformities. Oneâ fifth of rheumatologists and 29% of hand surgeons believed that drug therapy can correct hand deformities, which contradicts current evidence. Likewise, 30% and 14%, respectively, recommended surgery for earlyâ stage hand sequelae that do not meet current indications for surgery. Over 80% of surgeons and rheumatologists had no exposure to the other specialty during training and felt their training on the treatment of rheumatoid hand deformities was inadequate.ConclusionAlthough we found similar interspeciality disagreement in China as is seen in the United States, there appears to be less interaction through training and consultations. Our results also indicate potential deficits in training and unawareness of evidence and indications for rheumatoid hand surgery. These findings help to explain why surgery for rheumatoid hand deformities is rare in China; doctors have fewer opportunities to collaborate across specialties and may not be able to select appropriate candidates for surgery.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147075/1/apl12971.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147075/2/apl12971_am.pd

Dynamic Allocation without Money

We analyze the optimal design of dynamic mechanisms in the absence of transfers. The agent’s value evolves according to a two-state Markov chain. The designer uses future allocation decisions to elicit private information. We solve for the optimal allocation mechanism. Unlike with transfers, efficiency decreases over time. In the long run, polarization occurs. A simple implementation is provided. The agent is endowed with a “quantified entitlement,” corresponding to the number of units he is entitled to claim in a row

Dynamic Mechanisms without Money

We analyze the optimal design of dynamic mechanisms in the absence of transfers. The designer uses future allocation decisions to elicit private information. Values evolve according to a two-state Markov chain. We solve for the optimal allocation rule, which permits a simple implementation. Unlike with transfers, efficiency decreases over time, and both immiseration and its polar opposite are possible long-run outcomes. Considering the limiting environment in which time is continuous, we demonstrate that persistence hurts

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP) is proposed. Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints), the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency. Findings: In the process of the subproblems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality. Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop. Originality/value: The research provides an efficient scheduling method for the large-scale job shops, and will be helpful for the discrete manufacturing industry for improving the production efficiency and effectiveness