997 resultados para Yokohama-shi


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In practice, parallel-machine job-shop scheduling (PMJSS) is very useful in the development of standard modelling approaches and generic solution techniques for many real-world scheduling problems. In this paper, based on the analysis of structural properties in an extended disjunctive graph model, a hybrid shifting bottleneck procedure (HSBP) algorithm combined with Tabu Search metaheuristic algorithm is developed to deal with the PMJSS problem. The original-version SBP algorithm for the job-shop scheduling (JSS) has been significantly improved to solve the PMJSS problem with four novelties: i) a topological-sequence algorithm is proposed to decompose the PMJSS problem into a set of single-machine scheduling (SMS) and/or parallel-machine scheduling (PMS) subproblems; ii) a modified Carlier algorithm based on the proposed lemmas and the proofs is developed to solve the SMS subproblem; iii) the Jackson rule is extended to solve the PMS subproblem; iv) a Tabu Search metaheuristic algorithm is embedded under the framework of SBP to optimise the JSS and PMJSS cases. The computational experiments show that the proposed HSBP is very efficient in solving the JSS and PMJSS problems.

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This research deals with an innovative methodology for optimising the coal train scheduling problem. Based on our previously published work, generic solution techniques are developed by utilising a “toolbox” of standard well-solved standard scheduling problems. According to our analysis, the coal train scheduling problem can be basically modelled a Blocking Parallel-Machine Job-Shop Scheduling (BPMJSS) problem with some minor constraints. To construct the feasible train schedules, an innovative constructive algorithm called the SLEK algorithm is proposed. To optimise the train schedule, a three-stage hybrid algorithm called the SLEK-BIH-TS algorithm is developed based on the definition of a sophisticated neighbourhood structure under the mechanism of the Best-Insertion-Heuristic (BIH) algorithm and Tabu Search (TS) metaheuristic algorithm. A case study is performed for optimising a complex real-world coal rail system in Australia. A method to calculate the lower bound of the makespan is proposed to evaluate results. The results indicate that the proposed methodology is promising to find the optimal or near-optimal feasible train timetables of a coal rail system under network and terminal capacity constraints.

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In this paper, No-Wait, No-Buffer, Limited-Buffer, and Infinite-Buffer conditions for the flow-shop problem (FSP) have been investigated. These four different buffer conditions have been combined to generate a new class of scheduling problem, which is significant for modelling many real-world scheduling problems. A new heuristic algorithm is developed to solve this strongly NP-hard problem. Detailed numerical implementations have been analysed and promising results have been achieved.

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For the shop scheduling problems such as flow-shop, job-shop, open-shop, mixed-shop, and group-shop, most research focuses on optimizing the makespan under static conditions and does not take into consideration dynamic disturbances such as machine breakdown and new job arrivals. We regard the shop scheduling problem under static conditions as the static shop scheduling problem, while the shop scheduling problem with dynamic disturbances as the dynamic shop scheduling problem. In this paper, we analyze the characteristics of the dynamic shop scheduling problem when machine breakdown and new job arrivals occur, and present a framework to model the dynamic shop scheduling problem as a static group-shop-type scheduling problem. Using the proposed framework, we apply a metaheuristic proposed for solving the static shop scheduling problem to a number of dynamic shop scheduling benchmark problems. The results show that the metaheuristic methodology which has been successfully applied to the static shop scheduling problems can also be applied to solve the dynamic shop scheduling problem efficiently.

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Three types of shop scheduling problems, the flow shop, the job shop and the open shop scheduling problems, have been widely studied in the literature. However, very few articles address the group shop scheduling problem introduced in 1997, which is a general formulation that covers the three above mentioned shop scheduling problems and the mixed shop scheduling problem. In this paper, we apply tabu search to the group shop scheduling problem and evaluate the performance of the algorithm on a set of benchmark problems. The computational results show that our tabu search algorithm is typically more efficient and faster than the other methods proposed in the literature. Furthermore, the proposed tabu search method has found some new best solutions of the benchmark instances.

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In this paper, three metaheuristics are proposed for solving a class of job shop, open shop, and mixed shop scheduling problems. We evaluate the performance of the proposed algorithms by means of a set of Lawrence’s benchmark instances for the job shop problem, a set of randomly generated instances for the open shop problem, and a combined job shop and open shop test data for the mixed shop problem. The computational results show that the proposed algorithms perform extremely well on all these three types of shop scheduling problems. The results also reveal that the mixed shop problem is relatively easier to solve than the job shop problem due to the fact that the scheduling procedure becomes more flexible by the inclusion of more open shop jobs in the mixed shop.

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In this paper, we propose three meta-heuristic algorithms for the permutation flowshop (PFS) and the general flowshop (GFS) problems. Two different neighborhood structures are used for these two types of flowshop problem. For the PFS problem, an insertion neighborhood structure is used, while for the GFS problem, a critical-path neighborhood structure is adopted. To evaluate the performance of the proposed algorithms, two sets of problem instances are tested against the algorithms for both types of flowshop problems. The computational results show that the proposed meta-heuristic algorithms with insertion neighborhood for the PFS problem perform slightly better than the corresponding algorithms with critical-path neighborhood for the GFS problem. But in terms of computation time, the GFS algorithms are faster than the corresponding PFS algorithms.

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Digital human modeling (DHM), as a convenient and cost-effective tool, is increasingly incorporated into product and workplace design. In product design, it is predominantly used for the development of driver-vehicle systems. Most digital human modeling software tools, such as JACK, RAMSIS and DELMIA HUMANBUILDER provide functions to predict posture and positions for drivers with selected anthropometry according to SAE (Society of Automotive Engineers) Recommended Practices and other ergonomics guidelines. However, few studies have presented 2nd row passenger postural information, and digital human modeling of these passenger postures cannot be performed directly using the existing driver posture prediction functions. In this paper, the significant studies related to occupant posture and modeling were reviewed and a framework of determinants of driver vs. 2nd row occupant posture modeling was extracted. The determinants which are regarded as input factors for posture modeling include target population anthropometry, vehicle package geometry and seat design variables as well as task definitions. The differences between determinants of driver and 2nd row occupant posture models are significant, as driver posture modeling is primarily based on the position of the foot on the accelerator pedal (accelerator actuation point AAP, accelerator heel point AHP) and the hands on the steering wheel (steering wheel centre point A-Point). The objectives of this paper are aimed to investigate those differences between driver and passenger posture, and to supplement the existing parametric model for occupant posture prediction. With the guide of the framework, the associated input parameters of occupant digital human models of both driver and second row occupant will be identified. Beyond the existing occupant posture models, for example a driver posture model could be modified to predict second row occupant posture, by adjusting the associated input parameters introduced in this paper. This study combines results from a literature review and the theoretical modeling stage of a second row passenger posture prediction model project.

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Commonwealth Scientific and Industrial Research Organization (CSIRO) has recently conducted a technology demonstration of a novel fixed wireless broadband access system in rural Australia. The system is based on multi user multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM). It demonstrated an uplink of six simultaneous users with distances ranging from 10 m to 8.5 km from a central tower, achieving 20 bits s/Hz spectrum efficiency. This paper reports on the analysis of channel capacity and bit error probability simulation based on the measured MUMIMO-OFDM channels obtained during the demonstration, and their comparison with the results based on channels simulated by a novel geometric optics based channel model suitable for MU-MIMO OFDM in rural areas. Despite its simplicity, the model was found to predict channel capacity and bit error rate probability accurately for a typical MU-MIMO-OFDM deployment scenario.

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The factors affecting driving behaviors are various and interact simultaneously. Therefore, study of their correlations affecting on driving behaviors is of interest. This paper reports a questionnaire survey in China, focusing on the effect of Big-Five factors on speeding, drink driving, and distracted driving while Akers' social learning theory and Homel's deterrence theory were applied. The results showed that personalities had significant effect on speeding and drink driving; social factors had significant effect on speeding and distracted driving; deterrence had significant effect on speeding and drink driving; however, social learning theory did not contribute to drink driving; deterrence did not affect distracted driving. The results were discussed along with the limitation of this study.

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Human personality is an important component of psychological factors affecting pedestrian crossing. This paper reports a questionnaire survey on the effects of pedestrian personalities (including neuroticism, extraversion, openness, agreeableness and conscientiousness) on pedestrian violation in China. 675 feedbacks were obtained, of which 535 samples were valid for analysis. The results of the hierarchical regression analysis showed that educational level had significant effect on violation; agreeableness had significant effect on violation, conditional compliance and unconditional compliance; consciousness had significant effect on violation and conditional compliance; extraversion had significant effect on unconditional compliance; neuroticism had significant effect on violation; educational level had significant effect on violation. The results implied that psychological measures played a very important role in pedestrian safety.

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This paper reports an observation investigation of pedestrian crossing behaviors conducted at signalized crosswalks in urban areas in Singapore and Beijing on typical workdays. Each crosswalk was observed 3 times in different periods, i.e. normal hours, lunch hours, and rush hours. A total of 103,956 pedestrians were observed. The results showed that lane type, lane number, intersection type, and culture had significant effect on illegal pedestrian crossing in both cities; observation period had no significant effect on pedestrian violation in both cities; the violation rate in Singapore was lower than that in Beijing. However, observers reported that illegal crossing of vulnerable pedestrians, e.g. pregnant, the lame, old men and women, was more obvious in Singapore than that in Beijing. Evidence proved the hypothesis that the violations were related to pedestrians’ cognition of the definition of safety.

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Normative influences on road user behaviour have been well documented and include such things as personal, group, subjective and moral norms. Commonly, normative factors are examined within one cultural context, although a few examples of exploring the issue across cultures exist. Such examples add to our understanding of differences in perceptions of the normative factors that may exert influence on road users and can assist in determining whether successful road safety interventions in one location may be successful in another. Notably, the literature is relatively silent on such influences in countries experiencing rapidly escalating rates of motorization. China is one such country where new drivers are taking to the roads in unprecedented numbers and authorities are grappling with the associated challenges. This paper presents results from qualitative and quantitative research on self-reported driving speeds of car drivers and related issues in Australia and China. Focus group interviews and questionnaires conducted in each country examined normative factors that might influence driving in each cultural context. Qualitative findings indicated perceptions of community acceptance of speeding were present in both countries but appeared more widespread in China, yet quantitative results did not support this difference. Similarly, with regard to negative social feedback from speeding, qualitative findings suggested no embarrassment associated with speeding among Chinese participants and mixed results among Australian participants, yet quantitative results indicated greater embarrassment for Chinese drivers. This issue was also examined from the perspective of self-identity and findings were generally similar across both samples and appear related to whether it is important to be perceived as a skilled/safe driver by others. An interesting and important finding emerged with regard to how Chinese drivers may respond to questions about road safety issues if the answers might influence foreigners’ perceptions of China. In attempting to assess community norms associated with speeding, participants were asked to describe what they would tell a foreign visitor about the prevalence of speeding in China. Responses indicated that if asked by a foreigner, people may answer in a manner that portrayed China as a safe country (e.g., that drivers do not speed), irrespective of the actual situation. This ‘faking good for foreigners’ phenomenon highlights the importance of considering ‘face’ when conducting research in China – a concept absent from the road safety literature. An additional noteworthy finding that has been briefly described in the road safety literature is the importance and strength of the normative influence of social networks (guanxi) in China. The use of personal networks to assist in avoiding penalties for traffic violations was described by Chinese participants and is an area that could be addressed to strengthen the deterrent effect of traffic law enforcement. Overall, the findings suggest important considerations for developing and implementing road safety countermeasures in different cultural contexts.