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Automatic battery swap stations have been recently set widely in Taiwan while the system operators have found significant differences among the battery utilization rates of the stations. To reduce the battery idle time in the less visited stations, this study looks for effective persuasive design strategies that persuade users to choose the less visited stations. After useful persuasive strategies were collected from the related literature, eighteen feasible design strategies were proposed by considering the problem characteristics. A questionnaire survey was conducted to estimate the persuasion effects of the eighteen design strategies by using the storyboard method. The persuasive design strategies with higher persuasion effect are identified and recommended for reducing the gap of battery utilization rates. Furthermore, by using the statistical analysis like ANOVA to analyze the persuasion effect with respect to demographical variables such as gender and age, the results could help choose effective persuasive strategies for different target customer groups.

There is scientific research in several areas of knowledge that make use of the time-lapse technique. Tidal, rocks, and glaciers movements, which take up to months to occur, can be seen in a few seconds with this technique. Swamps, deserts, and even submerged areas are places of difficult access and need to be observed. There is always a high cost involved in the process of capturing time-lapse images. In this paper, a robotic tool is presented that meets the operational requirements to support these tasks. Among these new features is the ability to use idle time in the process of capturing images for this type of media. Its built-in camera is moved in different directions, being able to capture images for the generation of multiple time-lapse videos, using only one device. Because of this, this robotic tool is a facilitator to the construction of scientific, entertainment, and educational projects that make use of this type of unconventional data.

The multiprocessor scheduling problem is defined as follows: set of jobs have to be executed on parallel identical processors. For each job we know release time, processing time and delivery time. At most one job can be performed on every processor at a time, but all jobs may be simultaneously delivered. Preemption on processors is not allowed. The goal is to minimize the time, by which all tasks are delivered. Scheduling tasks among parallel processors is a NP-hard problem in the strong sense. The best known approximation algorithm is Jackson’s algorithm, which generates the list schedule by selecting the ready job with the largest delivery time. This algorithm generates no delay schedules. We define an IIT (inserted idle time) schedule as a feasible schedule in which a processor can be idle at a time when it could begin performing a ready job. The paper proposes the approximation inserted idle time algorithm for the multiprocessor scheduling. We proved that deviation of this algorithm from the optimum is smaller then twice the largest processing time. To illustrate the efficiency of our approach we compared two algorithms on randomly generated sets of jobs.

Prior work suggests that novice programmers are greatly impacted by the feedback provided by their programming environments. While some research has examined the impact of feedback on student learning in programming, there is no work (to our knowledge) that examines the impact of adaptive immediate feedback within programming environments on students' desire to persist in computer science (CS). In this paper, we integrate an adaptive immediate feedback (AIF) system into a block-based programming environment. Our AIF system is novel because it provides personalized positive and corrective feedback to students in real time as they work. In a controlled pilot study with novice high-school programmers, we show that our AIF system significantly increased students' intentions to persist in CS, and that students using AIF had greater engagement (as measured by their lower idle time) compared to students in the control condition. Further, we found evidence that the AIF system may improve student learning, as measured by student performance in a subsequent task without AIF. In interviews, students found the system fun and helpful, and reported feeling more focused and engaged. We hope this paper spurs more research on adaptive immediate feedback and the impact of programming environments on students' intentions to persist in CS.

In this paper, we consider the problem of the assembly line balancing, which allows us to find the assignment of each task that respects fixed constraints while optimizing the repair of working time. However, some other factors can affect productivity and workers, such as repetitive work, handling heavy loads. In this last case, workers in the assembly are subject to ergonomic risks. Besides, it is very important to reduce these risks which is the aim of this research where we attempt to show the importance of ergonomic of an assembly line and to prove the influence of its risks on an assembly line balancing problem. In fact, poor division of labor between stations can lead to unnecessary idle time and unnecessary additional costs for each part produced. In addition, the ergonomic risks can be included in inactivity and this underlines the importance of reducing this risk and its effect on the line. Thus, we expose in this paper a mathematical model to perform the assembly line balancing problem with ergonomic risks which are to reduce.

The paper deals with the question, “What is the Vehicle Routing Problem, Which Is Minimized Idle Time, and How Its Linear Programming Model Is Written?” In this study, a linear programming (LP) model has been developed for the vehicle routing problem (VRP) in order to minimize the total idle time (MIT). This problem was realized while managing the route operations of a company transporting long-distance passengers by bus in Turkey. The differences between this problem and other VRPs first arise from its objective function. It suggests that vehicles should work more because they make profit if they work. So, its objective function should be defined so as to minimize the sum of the idle time of those vehicles. Contrary to the VR problems examined so far, vehicles should work more, sometimes preferring long-distance routes as well. The other two differences pertain to constraints: some locations should be visited more than once in different time periods, and subtours could be allowed in some situations. In order to present the problem, a total of 34 routes of the company which belongs to one of the five subgroups were chosen for the samples. To solve this kind of problems, it is very important that exact methods, such as linear programming or branch and bound, should be used.

Currently, problem in assembly line has created so much attention, particularly in manufacturing area. Similar to this case study as they faced with problems regarding workstation in production line of electrical industry. There exist some cases where workstations in assembly line are experienced with bottleneck and suffered from high idle time. Thus, four heuristic methods are used for minimizing number or workstations and improve the bottleneck problems at the same time. In this case study, LCR, RPW and LPT have successfully minimized the number of workstations from 19 to 16. This solution has affected the layout of assembly line. Different from SPT that manage to improve the bottleneck among workstations by reducing number of workstations from 19 to 17 without changing the line layout. Therefore, both solution has brought an option for an engineer to choose which decision to be used in this assembly line in order to increase the line efficiency.

Flowshop scheduling problem with bicriteria of makespan and idle time under no-wait constraint is addressed in this paper. The problem of flowshop scheduling environment with criteria of minimum makespan and idle time is NP-hard under no-wait constraint; therefore, heuristic algorithms are key to obtain the solutions of these problems near to optimal. The paper describes a heuristic technique to schedule the sequence of n jobs on m machine in no-wait flowshop environment with objective of minimizing both makespan and idle time. Computation results show the better solution quality of proposed heuristic approach over existing constructive heuristics.

Diese Arbeit beschäftigt sich mit dem Thema der Messbarkeit der Auswirkungen der Lean Methode Last-Planner am Beispiel des Neubaus von Wohnungen in Wien. Heutzutage kommen Lean-Methoden immer häufiger zum Einsatz auf Baustellen. Die Anwendung wird aufgrund der bekannten positiven Auswirkungen, wie zum Beispiel die Erhöhung der Effizienz, Kostenersparnis oder Termineinhaltung immer beliebter. Die positiven Auswirkungen sind deutlich erkennbar, jedoch stellt sich die Frage, ob diese wirklich bloß auf die Anwendung der Lean Methode oder ob diese zumindest zu einem gewissen Anteil auf andere einflussnehmende Faktoren zurückzuführen sind. Um diesen Nachweis erbringen zu können, müssten die besagten Auswirkungen auf zwei vergleichbaren Baustellen gemessen werden, wobei eine der beiden die Lean Methode anwendet und die andere nicht. Aufgrund der unterschiedlichen Rahmenbedingungen und der Merkmale eines Bauprojekts (Individualität, zeitliche Begrenzung, begrenzte Ressourcen, Einzigartigkeit, Komplexität) ist die Vergleichbarkeit von zwei Baustellen nicht einfach, da die Ergebnisse letztendlich nicht ausreichend aussagekräftig wären. Der in dieser Arbeit verfolgte Ansatz beruht darauf, die Verschwendungen (Acht Verschwendungsarten laut Lean Construction) zu messen, um nachzuweisen, dass die positiven Auswirkungen durch die Lean Methode ausgelöst werden. Dabei wurden drei von den acht Verschwendungsarten ausgewählt und darauf basierend drei Kennzahlen definiert. Die wissenschaftliche Fragestellung lautet: Können die Auswirkungen der Lean Methode Taktplanung/Taktsteuerung am Beispiel des Neubaus von Wohnungen in Wien anhand von Kennzahlen messbar gemacht werden? Im nächsten Schritt wurden Personen, die auf der Baustelle arbeiten, zu dieser Thematik befragt. Hier wurde unter anderem das Bewusstsein für die Verschwendungsarten erfasst, aber auch nach der Möglichkeit der Messungen dieser Kennzahlen auf der Baustelle gefragt. Dies wurde in Form eines Fragebogens durchgeführt. Bedingt durch die Corona-Krise 2020 wurden diese Fragebögen gemeinsam mit den Teilnehmern über Telefon- oder Videoanruf ausgefüllt. Aufgrund der bereits genannten Krise reduzierte sich auch die Teilnehmerzahl. Die Bewertung der einzelnen Fragen führte manchmal erwartungsgemäß zu sehr klaren Ergebnissen, andererseits ergaben sich jedoch auch einige paradoxe Resultate, obwohl bestimmte Fragen umformuliert wurden, um die Authentizität der gegebenen Antworten bewerten zu können. Nach kritischer Betrachtung und Analyse der Auswertung lässt sich zusammengefasst folgendes sagen: Das Ergebnis der Befragungen deutet darauf hin, dass die Möglichkeit der Messbarkeit von definierten Kennzahlen unter bestimmten Voraussetzungen gegeben ist. Diese Voraussetzungen sind beispielweise die Definition der Kennzahlen und der Vorgangsweise der Messung vor Baubeginn. Eine weitere Voraussetzung ist die Aufbereitung und Dokumentation der nötigen Daten für die Messung der Kennzahlen in einer bestimmten Form. Hierbei könnte die Digitalisierung auf der Baustelle eine große Rolle spielen. Abschließend kann aus dieser Arbeit abgeleitet werden, dass die nötigen Daten für die Nachweisführung der Rückführbarkeit der positiven Auswirkungen auf die Lean Methode Last-Planner vorhanden sind, diese jedoch in einer bestimmten Form im Laufe der Baustelle dokumentiert werden müssen, um die zuvor definierten Kennzahlen messen zu können. This thesis engages with the topic of measurability of the effects of the Lean Method Last-Planner using new build apartments as an example in Vienna. Nowadays, Lean methods are increasingly used on construction sites. The use of Lean methods has become more and more popular due to the well-known positive effects such as efficiency, cost savings, or the adherence to project deadlines. Furthermore, positive effects are clearly recognizable. However, the question arises whether the positive effects are truly attributed to the application of the lean method, or whether this acknowledgment is caused, to a certain extent, by other influencing factors. In order to provide evidence for this, the effects would have to be measured on two comparable construction sites, one location applying the Lean method and the other not. Yet, it is difficult to precisely compare two construction sites with one another due to the different parameters as well as the characteristics of a building project such as individuality, deadlines, limited resources, uniqueness, and complexity. Hence, the results would ultimately have no sufficient meaning. The approach of this thesis is based on measuring the 8 Wastes of Lean Construction in order to demonstrate that positive effects are actually triggered by the Lean method. Three of the 8 Wastes of Lean Construction were selected and based on them three key figures were defined. Therefore, the scientific query is: can the effects of the lean method cycle planning/ cycle control be measured by using the example of new build apartments in Vienna through the key figures? Thus, a group of workers and employees on the construction site were asked about this topic. Among other things, moreover, the awareness of the types of waste was questioned, but also the possibility of measuring the key figures on the construction site. This was done in the form of a questionnaire. Due to the COVID-19 crisis in 2020, these questionnaires were filled out together with the participants via telephone or video call. As a result of the aforementioned crisis, unfortunately the number of planned participants also decreased. The evaluation of the individual questions sometimes delivered very clear results, as expected. On other hand some paradoxical results also emerged, although some questions were rephrased to evaluate the authenticity of the answers given. After critically analyzing the results, the following can be summarized: the results of the surveys indicate that it is possible to measure defined key figures under certain conditions. These prerequisites are, for example, the definition of the key figures and the procedure of measurement prior to construction begin. Another prerequisite is, the preparation and documentation of necessary data, in a certain register, for the measurement of the key figures. Here, a digitalization on the construction site could and will play a major role in the future. In conclusion, one can deduce that necessary data verifying the traceability of the positive effects to the Lean Method Last Planner are available. Nonetheless, this data must be documented, again through a certain register, during the construction site in order to correctly measure the previously defined key figures. vorgelegt von: Katrin Nasr Auch als Printexemplar verfügbar Masterarbeit Wien, FH Campus Wien 2020

The jobs processed in cloud computing systems may consist of multiple associated tasks which need to be executed under ordering constraints. The tasks of each job are run on different nodes, and communication is required to transfer data between nodes. The processing and communication capacities of different components have great heterogeneity. For multiple jobs, simple task scheduling policies cannot fully utilize cloud resources and hence may degrade the performance of job processing. Therefore, careful multi-job task scheduling is critical to achieve efficient job processing. The performance of existing research on associated task scheduling for multiple jobs needs to be improved. In this paper, we tackle the problem of associated task scheduling of multiple jobs with the aim to minimize jobs’ makespan. We propose a task Duplication and Insertion based List Scheduling algorithm (DILS) which incorporates dynamic finish time prediction, task replication, and task insertion. The algorithm dynamically schedules the tasks based on the finish time of scheduled tasks, replicates some of the tasks on different nodes, and inserts the tasks into idle time slots to expedite successive task execution. We finally conduct experiments through simulations. Experimental results demonstrate that the proposed algorithm can effectively reduce the jobs’ makespan.

The article is aimed at determining the expediency of rational option choosing by reverse transportation loading during goods delivery in intercity directions. Five possible alternatives are proposed to truck returns while waiting for backloading at first step of researches. An integrated criterion is selected as a condition for rational option choosing of truck returns. It is a synergistic effect for carriers and customers of transport services. Therefore, rational option search to return vehicles with reverse loading is to choose the best values: maximum cost-effectiveness of transportation and minimum delivery period. The result is a compromise solution between carrier and customer interests. Such an approach will allow transport companies to expand their influence sphere and find new permanent clients.

In this present work, an attempt is made to solve FMS scheduling problem by considering the multiobjective using Modified Cuckoos Search Algorithm. Combined Objective Function (COF) is formulated by considering two objectives with equal weightage i.e., minimizing the machine idle time and minimizing the penalty cost. The problem considered is 43 jobs need to be manufactured by processing on 16 machines is taken from literature. Matlab program is written to calculate COF value and for finding best sequence, COF value MCS algorithm is implemented. Best sequence and COF values obtained by MCS algorithm are compared with values obtained by other Algorithms like SPT, LPT, PSO, GA & CS. It is observed that sequence obtained by Modified Cuckoos Search Algorithm is giving better COF values.

In static-deterministic flow shop scheduling, solution algorithms are often tested by problem instances with uniformly distributed processing times. However, there are scheduling problems where a certain structure, variability or distribution of processing times appear. While the influence of these aspects on common objectives, like makespan and total completion time, has been discussed intensively, the efficiency-oriented objectives core idle time and core waiting time have not been taken into account so far. Therefore, a first computational study using complete enumeration is provided to analyze the influence of different structures of processing times on core idle time and core waiting time. The results show that in some cases an increased variability of processing times can lead to easier solvable problems.

The forward Kolmogorov system for a general nonstationary Markovian queueing model with possible batch arrivals, possible catastrophes and state-dependent control at idle time is considered. We obtain upper bounds on the rate of convergence for corresponding models (nonstationary \(M^X/M_n/1\) queue without catastrophes with the special resurrection intensities and general nonstationary \(M^X/M_n/1\) queue with mass arrivals and catastrophes) and apply these estimates for some specific situations. Examples with given parameters are considered and corresponding plots are constructed.

The e-hailing platforms have transformed the way people travel, live, and socialize. The efficiency of the platform is substantially influenced by the distribution differences between demands and supplies in the city. Therefore, an appropriate reposition vehicle strategy can significantly balance this distribution difference, which will promote platform benefits, customer goodwill and greatly alleviate traffic congestions. Due to the complicated relationship between vehicles and the temporal correlation of reposition actions, it is a challenging task to reposition vehicles in the city. Existing studies mostly focus on individual drivers that can hardly capture the relationship between drivers and long-term variations of demands and supplies in the city. In this paper, we introduce the reinforcement learning with geographic information and propose a geographic-based multi-agent deep deterministic policy gradient algorithm (gbMADDPG). The algorithm is driver-centric which takes the passenger searching time as an optimization goal to reduce the idle time of vehicles. We will demonstrate the effectiveness of our proposed algorithm framework through simulation experiments based on real data.

Dynamic pricing can be used for better fleet distribution in free-floating vehicle sharing (FFVS), and thus increase utilization and revenue for the provider by reducing supply-demand asymmetry. Supply-demand asymmetry refers to the existence of an undersupply of vehicles at some locations at the same time as underutilization of vehicles at other locations. We propose to use dynamic pricing as an instrument to incentivize users to rebalance these vehicles from low demand locations to high demand locations. Despite significant research in rebalancing vehicle sharing, the literature so far lacks experimental results on dynamic pricing in free-floating vehicle sharing. We propose to use an algorithm that minimizes the differences in the idle time of vehicles. The algorithm is tested in a real-life experiment that was conducted in cooperation with an FFVS provider. The results of the experiment are not statistically significant, but they clearly indicate that even slight differences in pricing and a simple algorithm can already influence user-behavior to counter supply-demand asymmetry. Improving the existing algorithm with more experimental research is advised to further uncover the potential of this strategy.

The condition of the motor oil in civilian cars is difficult to monitor; hence, we propose a method to evaluate the degree of degradation of motor oil using an on-board diagnostic (OBD) system. Three civilian cars and four motor oils (containing mineral oils and synthetic oils) were subjected to five groups of road tests under urban traffic and high-way conditions. The operation information, oil service time, mileage, engine operation time, idle time of the engine, and number of start-ups of the engine were obtained using the proposed OBD system. Physiochemical properties and changes in the components of motor oils during road tests were analyzed in laboratory. The theoretical model of the comprehensive indicators of driving parameters and oil properties were established. The proposed method was successfully applied to different cars, motor oils, and operating conditions in road tests. All the theoretical models had high accuracy and precision. Herein, we provide a method to monitor the oil condition with real-time driving parameters and provide a reference for end users to change their motor oil reasonably.

Metode penjadwalan linier cocok untuk proyek dengan aktivitas sederhana, dan repetitif dengan jumlah unit yang tipikal, seperti proyek jalan, irigasi, tunnel, apartment, dan perumahan sederhana. Pada penelitian ini dilakukan pemodelan penjadwalan linier proyek pembangunan perumahan sebanyak 50 unit tipikal. Simulasi alokasi sumber daya manusia dan penggunaan buffer agar penggunaan sumber daya manusia dapat seefisien mungkin. Hasil penelitian diperoleh bahwa simulasi ke-8 dengan menggunakan buffer memiliki durasi 314 hari dengan 18 kelompok kerja, apabila dibandingkan dengan simulasi ke-9 tanpa menggunakan buffer memiliki durasi 180 hari dan idle time 134 hari inefisiensi 1522 orang hari. Linear scheduling method is suitable for projects with repetitive activities, as well as tipical mass product units such as a road, apartment, and residential housings. In this research linear schedule modeling was carried out on residential typical housings project of 50 units. The simulation of linear scheduling is to minimize the idle times by using time buffers and human resources allocation so that the usage of human resources can be as efficient as possible. The research findings show that the 8th simulation by using buffers has a project duration of 314 days were chosen with 18 working groups, compares to 9th simulation without buffers that has a duration of 180 days and 134 days of idle time which with 1522 man day of inefficient.

This research was conducted in a cooperation namely KOPSAE, located in three villages, Jurang Jero, Pujon Lor, and Sebaluh, distric of Pujon. Malang, East Java. The research objective is to investigate the women involvement in improving family life of diery farmer in tose villages and to evaluate the women’s contribution in their family’s revenue. This research results can be used by East Java Animal Husbandary Office, financial institutions, cooperative enterprises, and other external parties in determining prolicies for supervision and improvement of farm business in rural areas. Data are collected through survey. Population used are 40 families who own cows.The result shows that women have potential roles in improving the family’s revenues. The women contribution is approximately 44,99% of total family’s revenues. The women allocate their time about 1-2 hours a day in diery family activities, meanwhile, men spent about 2-4 hours a day. It appears that supervision is still needed for using their idle time in order to improve their skills as well as their revenues.

This research was conducted in a cooperation namely KOPSAE, located in three villages, Jurang Jero, Pujon Lor, and Sebaluh, distric of Pujon. Malang, East Java. The research objective is to investigate the women involvement in improving family life of diery farmer in tose villages and to evaluate the women’s contribution in their family’s revenue. This research results can be used by East Java Animal Husbandary Office, financial institutions, cooperative enterprises, and other external parties in determining prolicies for supervision and improvement of farm business in rural areas. Data are collected through survey. Population used are 40 families who own cows.The result shows that women have potential roles in improving the family’s revenues. The women contribution is approximately 44,99% of total family’s revenues. The women allocate their time about 1-2 hours a day in diery family activities, meanwhile, men spent about 2-4 hours a day. It appears that supervision is still needed for using their idle time in order to improve their skills as well as their revenues.

Idle times of shunting locomotives were measured in nineteen Polish industrial sidings and analyzed. The current locomotive owner’s regulations propose 30 min as the maximum idle time for shunting locomotives. Research shows that the size of a single idle time gap ranges from seconds (most frequent) to 4 h (during winter), but 95% of observed idle times are shorter than 4–11 min (for different types of locomotives). 75% of the idle times cases are less than 1.5 min (47 s if counted only for SM31 locomotive). We fit the distribution of the measured idle times to theoretical distributions, obtaining the best fit for the Pareto type II. If the diesel engine idle time lasts for 9 min then the probability that the given engine will stay in the idle mode for the subsequent 8 min is large, namely, greater than 0.6. These results go along with Weaver (2006). He concludes that if the locomotive idling lasts longer than 8 min then it is more energy efficient to turn off and restart a modern locomotive. Letting it idle for the whole time produces more emissions. If the frequent turning on and off does not reduce the engine life we propose to turn off the locomotive engine after 10 min of unnecessary idling. Automatic Engine Start Stop system (AESS) could (in addition to its main tasks) send reports to the locomotive owner if the engineer deactivates this system too many times.

The ways of improving performance of the harvesting-transportation system for harvesting grain crops by applying means for positioning and monitoring vehicles in the fi eld were identifi ed. The studies were conducted in agricultural enterprises of the forest-steppe zone of Novosibirsk region from 2007 to 2017 during eleven harvesting periods. The grain yields amounted to 4.2 tonnes per ha, the distance of transportation was up to 25 km. Taking into account the peculiarities of the harvesting-transportation system due to remoteness of the fi elds, the time for moving from one harvester to the next, unloading a harvester and a heavy-duty trailer-loader, an expression was obtained to determine the time cycle of the trailer reload scheme for handling the transport service with the use of positioning and monitoring means. It was established that when performing harvesting and transporting in the reloading scheme with the application of positioning systems and monitoring technical means and the use of heavy-duty trailer-loader for transporting distances of over 12 km and yields of over 2 tonnes per ha, the idle time of harvesters and vehicles decreased. The need in vehicles was also reduced; effi ciency of high-performance combine harvesters increased by 10-25%; the coeffi cient of threading e = 0.92; performance of harvesting-transportation system as a whole increased by 9-18 %.

Context. The problems of cost minimizing for the delivery of raw materials, fuel and materials, while meeting all the requirements of end user in terms of transportation, condition, quality and amount of the cargo, the compliance of the rolling stock with the equipment of unloading points, etc. are still the key problems of efficient transportation management. A problem to improve a system controlling a process of cargo operations performance at industrial enterprises during the cold season, when well-managed process is considerably complicated by the influence of stochastic fluctuations in the environmental temperature remains to be topical one. Delivery cost experiences significant increase due to the growth of power consumption for the cargo defrosting. The objective of the paper is to improve a system controlling a process of railcars unloading in terms of expectations of the negative changes in the temperature mode owing to optimization of the railcars distribution among the unloading points by the criterion of the idle time minimization. Method. Two temperature modes are singled out: standard operating mode in terms of positive temperatures and a mode of necessity to recover looseness of frozen cargos. The method of operative disbalance of incoming cargo flows has been developed to provide more rational distribution of cargos within cargo loading/unloading complexes during the periods of temperature changes being typical for Ukrainian climate. A new procedure to solve dynamic transportation problem with the varying intensity factor of incoming cargo flows in terms of time has been developed. A factor of minimum period for cargo operation has been proposed as an optimization criterion. Results. Methodology has been developed basing upon a method of operative disbalance of incoming cargo flows. Experiments concerning the methodology application have been carried out to improve the system controlling the process of railcars unloading in terms of changes in temperature mode. Conclusions. Analysis of the research results has shown that the proposed approach decreases significantly the idle time of the railcars in terms of temperature mode changes, reduces expenses connected with the railcars use as well as the expenses connected with the recovery cargo looseness and operation of locomotives.

Although the reason is not clear, mileage is commonly recommended as an indicator to evaluate the oil drain interval of a car. This paper tries to investigate whether the mileage is the most suitable indicator to evaluate the oil drain interval based on scientific experiments and data analysis method. Three civilian cars and motor oils (contained mineral oil, semisynthetic oil, and synthetic oil) were subjected to road tests under urban traffic condition. The real-time driving parameters comprising speed, mileage, idle time, engine operation time, and number of starts were obtained by on-board diagnostic system. Synchronous oil samples were collected about every 30 days. The physicochemical properties and component changes of experimental oils were analyzed in laboratory. The effects of driving parameters on oil properties were studied with the improved grey relational analysis method. The results show that the influencing factors of driving parameters on motor oil degradation were different in different experimental cars. The influence of mileage on oil degradation was not obvious. The idle time of engine, engine operation time, and number of starts were the three most significantly influential factors on oil deterioration after comprehensive analysis of the three experimental cars.

For electric taxicabs, the idle time spent on cruising for passengers, seeking chargers, and charging is wasteful. Previous works can only save cruising time through better routing, or charger seeking and charging time through proper charger deployment, but not for both. With the advancement of wireless charging techniques, efficient opportunistic charging of electric vehicles at their parked positions becomes possible. This enables a taxicab to get charged while waiting for the next passenger. In this paper, we present an opportunistic wireless charger deployment scheme in a city, which both maximizes the taxicabs' opportunity of picking up passengers at the chargers and supports the taxicabs' continuous operability on roads, while minimizing the total deployment cost. We studied a metropolitan-scale taxicab dataset on several factors important for deploying wireless chargers and determining the numbers of the chargers in the regions: the number of passengers, the functionalities of buildings, and the frequency of passenger appearance in a region, and taxicab traffic flows in a city. Then, we formulate a multi-objective optimization problem and find the solution. Our trace-driven experiments demonstrate the superior performance of our scheme over other representative methods in terms of reducing idle time and supporting the operability of the taxicabs.

In order to reduce the fuel consumption of idling, lots of vehicles are equipped with idle start–stop system. In the actual traffic situation, heavy traffic result in frequent short time idle stop, which causes two major problems with the existing start–stop system, frequent starting and stopping and invalid stopping. That not only exacerbates component wear but also makes fuel efficiency worse. Aiming at this problem, an improved Markov model for idle time prediction based on spatiotemporal learning is proposed. Based on original Markov model, related training subset for training model is determined according time and space information, which could increase prediction accuracy by reducing the redundant noisy data. Experiments conducted on real urban dataset demonstrate that our proposed model could get better performance, the F1-measure increased by 8.0%. Start–stop strategy using the prediction method can make invalid idling reduced by 35.1%, which can effectively avoid invalid idling and obtain a reduction of frequent starting and stopping.

This research evaluates the efficiency of blistering lines over a 2-year period starting January 2013 till December 2014 using data envelopment analysis models. The planned production quantity in units, defect quantity in units, and idle time in units are selected as inputs. The actual produced quantity in units is the output measure. The data are then normalized using the min–max normalization. Six windows are formed, and then the technical, pure technical, and scale efficiency are calculated for three identical blistering machines lines, BL1, BL2, and BL3, in each year. Results showed significant reductions in technical (TIE), pure technical (PTIE) inefficiency, and scale inefficiency (SIE) scores in year 2014. For BL1, the average TIE, PTIE, and SIE are reduced from 0.1152 to 0.0477, 0.0751 to 0.0176, and 0.0429 to 0.0304, respectively. For BL2, the average TIE, PTIE, SIE are reduced from 0.0968 to 0.0282, 0.0514 to 0.0133, and 0.0486 to 0.0149, respectively. Finally, for BL3, the average TIE, PTIE, SIE are reduced from 0.0936 to 0.0527, 0.0396 to 0.0154, and 0.0556 to 0.0380, respectively. In practice, the sources of TIE are mainly failure to operate at most productive scale size (SIE) and/or the poor input utilization (PTIE). In conclusion, the research results provide valuable feedback on how to improve efficiency, utilize resources, and effectively manage production lines.

Hyper-local food delivery involves delivering food from neighborhood eateries by gig workers, mostly using motorized two-wheelers. An accurate assessment of the negative external costs will help decision-makers sustainably regulate such services. As a first step, this research develops an agent-based simulation of a hyper-local food delivery system. Using primary data from Kolkata, India, the simulator estimates the fleet size, the average distance traveled per order, the average number of orders delivered and the average idle time spent by a delivery worker, at varying order volumes. The negative externalities estimated are the emissions per order and the spatio-temporal parking demand generated by the delivery fleet. The results show that at an order volume of 2100, on average, the distance traveled per order is 5.85 km, the orders delivered per worker is 15, the idle time spent is 59.2% and each delivery results in the emission of 163.08 gm CO2.