Train schedule coordination at an interchange station through agent negotiation

In open railway markets, coordinating train schedules at an interchange station requires negotiation between two independent train operating companies to resolve their operational conflicts. This paper models the stakeholders as software agents and proposes an agent negotiation model to study their interaction. Three negotiation strategies have been devised to represent the possible objectives of the stakeholders, and they determine the behavior in proposing offers to the proponent. Empirical simulation results confirm that the use of the proposed negotiation strategies lead to outcomes that are consistent with the objectives of the stakeholders

Theory of constraints (TOC) production and manufacturing performance

This paper is based on an empirical study of the relationship between Theory of Constraints (TOC) production and operational performance in manufacturing plants. The study uses a survey questionnaire to collect data from a sample of 61 European firms which have implemented the TOC approach. Analysis of variance (ANOVA) technique and regression models have been employed to test the research hypotheses. The results detect many differences and similarities in adoption of TOC practices across the countries and suggest that manufacturing managers should consider adopting some TOC practices instead of others. In particular the Drum-buffer-rope methodology, the development of a Master Production Schedule based on constraints and the use of Non-constraint resources with excess capacity are among the most important practices to enhance competitive performance of manufacturing plants

An integrated approach for requirement selection and scheduling in software release planning

It is essential for product software companies to decide which requirements should be included in the next release and to make an appropriate time plan of the development project. Compared to the extensive research done on requirement selection, very little research has been performed on time scheduling. In this paper, we introduce two integer linear programming models that integrate time scheduling into software release planning. Given the resource and precedence constraints, our first model provides a schedule for developing the requirements such that the project duration is minimized. Our second model combines requirement selection and scheduling, so that it not only maximizes revenues but also simultaneously calculates an on-time-delivery project schedule. Since requirement dependencies are essential for scheduling the development process, we present a more detailed analysis of these dependencies. Furthermore, we present two mechanisms that facilitate dynamic adaptation for over-estimation or under-estimation of revenues or processing time, one of which includes the Scrum methodology. Finally, several simulations based on real-life data are performed. The results of these simulations indicate that requirement dependency can significantly influence the requirement selection and the corresponding project plan. Moreover, the model for combined requirement selection and scheduling outperforms the sequential selection and scheduling approach in terms of efficiency and on-time delivery. \u

Optimal irrigation water allocation using a genetic algorithm under various weather conditions

Growing water scarcity, due to growing populations and varying natural conditions, puts pressure on irrigation systems, which often are the main consumptive water users. Therefore, water resources management to improve the allocation of limited water supplies is essential. In this study, a non-linear programming optimization model with an integrated soil/water balance is developed to determine the optimal reservoir release policies and the optimal cropping pattern around Doroudzan Dam in the South-West of Iran. The proposed model was solved using a genetic algorithm (GA). Four weather conditions were identified by combining the probability levels of rainfall, evapotranspiration and inflow. Moreover, two irrigation strategies, full irrigation and deficit irrigation were modeled under each weather condition. The results indicate that for all weather conditions the total farm income and the total cropped area under deficit irrigation were larger than those under full irrigation. In addition, our results show that when the weather conditions and the availability of water changes the optimal area under corn and sugar beet decreases sharply. In contrast, the change in area cropped with wheat is small. It is concluded that the optimization approach has been successfully applied to Doroudzan Dam region. Thus, decision makers and water authorities can use it as an effective tool for such large and complex irrigation planning problems

Does Order Negotiation Improve The Job-Shop Workload Control?

Work flows in a job-shop are determined not only by the release load and the time between release factors, but also by the number of accepted orders. There has been extensive research on workload and input-output control aiming at improving the performance of manufacturing operations in job-shops. This paper explores the idea of controlling the workload since the acceptance/rejection of orders stage. A new acceptance/rejection rule is proposed, and tests are conducted to study the sensitivity of job-shop performance to different order acceptance parameters, like the tolerance of the workload limit and the due date extension acceptance. It also evaluates the effect of the negotiation phase of the proposed acceptance rule on the job-shop performance using a simulation model of a generic random job-shop. The extensive simulation experiments allow us to conclude that having a negotiation phase prior to rejection improves almost all workload performance measures. We also conclude that different tolerances of the workload limit affect slightly the performance of the job-shop.job shop, order negotiation, workload control

Lagrangian study of surface transport in the Kuroshio Extension area based on simulation of propagation of Fukushima-derived radionuclides

Lagrangian approach is applied to study near-surface large-scale transport in the Kuroshio Extension area using a simulation with synthetic particles advected by AVISO altimetric velocity field. A material line technique is applied to find the origin of water masses in cold-core cyclonic rings pinched off from the jet in summer 2011. Tracking and Lagrangian maps provide the evidence of cross-jet transport. Fukushima derived caesium isotopes are used as Lagrangian tracers to study transport and mixing in the area a few months after the March of 2011 tsunami that caused a heavy damage of the Fukushima nuclear power plant (FNPP). Tracking maps are computed to trace the origin of water parcels with measured levels of Cs-134 and Cs-137 concentrations collected in two R/V cruises in June and July 2011 in the large area of the Northwest Pacific. It is shown that Lagrangian simulation is useful to finding the surface areas that are potentially dangerous due to the risk of radioactive contamination. The results of simulation are supported by tracks of the surface drifters which were deployed in the area

Effect of flow forecasting quality on benefits of reservoir operation - a case study for the Geheyan reservoir (China)

This paper presents a methodology to determine the effect of flow forecasting quality on the benefits of reservoir operation. The benefits are calculated in terms of the electricity generated, and the quality of the flow forecasting is defined in terms of lead time and accuracy of the forecasts. In order to determine such an effect, an optimization model for reservoir operation was developed which consists of two sub-models: a long-term (monthly) and a short-term (daily) optimization sub-model. A methodology was developed to couple these two sub-models, so that both short-term benefits (time span in the order of the flow forecasting lead time) and long-term benefits (one year) were considered and balanced. Both sub-models use Discretized Dynamic Programming (DDP) as their optimization algorithms. The Geheyan reservoir on the Qingjiang River in China was taken as case study. Observed (from the 1997 hydrological year) and forecasted flow series were used to calculate the benefits. Forecasted flow series were created by adding noises to the observed series. Different magnitudes of noise reflected different levels of forecasting accuracies. The results reveal, first of all, a threshold lead time of 33 days, beyond which further extension of the forecasting lead time will not lead to a significant increase in benefits. Secondly, for lead times shorter than 33 days, a longer lead time will generally lead to a higher benefit. Thirdly, a perfect inflow forecasting with a lead time of 4 days will realize 87% of the theoretical maximum electricity generated in one year. Fourthly, for a certain lead time, more accurate forecasting leads to higher benefits. For inflow forecasting with a fixed lead time of 4 days and different forecasting accuracies, the benefits can increase by 5 to 9% compared to the actual operation results. It is concluded that the definition of the appropriate lead time will depend mainly on the physical conditions of the basin and on the characteristics of the reservoir. The derived threshold lead time (33 days) gives a theoretical upper limit for the extension of forecasting lead time. Criteria for the appropriate forecasting accuracy for a specific feasible lead-time should be defined from the benefit-accuracy relationship, starting from setting a preferred benefit level, in terms of percentage of the theoretical maximum. Inflow forecasting with a higher accuracy does not always increase the benefits, because these also depend on the operation strategies of the reservoir.\u