Start Times Of Activities Research Articles

Robust Local Search for Solving RCPSP/max with Durational Uncertainty

Scheduling problems in manufacturing, logistics and project management have frequently been modeled using the framework of Resource Constrained Project Scheduling Problems with minimum and maximum time lags (RCPSP/max). Due to the importance of these problems, providing scalable solution schedules for RCPSP/max problems is a topic of extensive research. However, all existing methods for solving RCPSP/max assume that durations of activities are known with certainty, an assumption that does not hold in real world scheduling problems where unexpected external events such as manpower availability, weather changes, etc. lead to delays or advances in completion of activities. Thus, in this paper, our focus is on providing a scalable method for solving RCPSP/max problems with durational uncertainty. To that end, we introduce the robust local search method consisting of three key ideas: (a) Introducing and studying the properties of two decision rule approximations used to compute start times of activities with respect to dynamic realizations of the durational uncertainty; (b) Deriving the expression for robust makespan of an execution strategy based on decision rule approximations; and (c) A robust local search mechanism to efficiently compute activity execution strategies that are robust against durational uncertainty. Furthermore, we also provide enhancements to local search that exploit temporal dependencies between activities. Our experimental results illustrate that robust local search is able to provide robust execution strategies efficiently.

Research on Resource Optimization of Block Erection Procedure Based on PSO

The resource optimization of ship erection procedure is a classic NP-hard problem. Through analyzing the character about this problem, an algorithm model of Particle Swarm Optimization (PSO) is proposed. Particle’s coordinate in the particle swarm is used for the activity’s actual start time and methods for resource leveling based on dynamic time variance are designed. Evolution equations based on integer compute rule is introduced to improve the converging speed and accuracy of traditional PSO algorithm. The last simulation experiment with the practical data demonstrates the feasibility and the effectiveness of the improved PSO algorithm by comparisons and analyses.

Investigating the Role of Social Networks in Start Time and Duration of Activities

In the context of improving understanding and modeling the capabilities of activity-scheduling processes in travel behavior, this paper explores the role of social networks in the start time and the duration of social activities. The study was performed with a trivariate joint econometric model that was capable of capturing the correlation between unobserved influential factors causing the endogeneity of these three key decisions. The model captures the relevance not only of sociodemographic variables but also of the social network dimension for travelers, or the with whom variable, that is, individuals with whom travelers perform social activities. A particularly relevant case is the role of travel time to social activities, which has a positive effect on longer durations and late start times and which acts as a link between these two basic dimensions (start time and duration) of activity scheduling. The results confirm the relevance of the social context in an episode's temporal characteristics and illustrate aspects that future activity-based travel demand models should incorporate to be able to capture the socializing side of mobility decisions.

Software process control model based on critical path method

A software process control model based on critical path method was presented for enhancing the software process controlling to guarantee the product quality.The model is based on the topological structure of the process activities.Under the precondition of ensuring the time limit for the project and the resource requirement of the critical activities,the start time of the other activities were controlled by a mathematical model with the target of making the total resource cost less and the starting of the activities much earlier under the optimal resource cost.Under the constraint of the optimal resource cost,an algorithm based on resource competition chain was also promoted to update the float information of the uncritical activities.At last,the experimental results show the model is feasible and effective.

Fuzzy finish time modeling for project scheduling

This research aims at developing a new fuzzy activity finish time estimation model for project scheduling management. With the application of the fuzzy quality function deployment (FQFD) and fuzzy analytic hierarchy process (FAHP) methods, the degree of fuzziness for every project activity is calculated in accordance with considerations of project uncertainties. These uncertainties are measured by the risk level of such project-related characteristics as time limit, activity start time, budget, manpower, technological difficulty, and facility requirements. In this paper, rather than applying the de-fuzzification technique to obtain the crisp activity duration for project scheduling, the fuzzy finish time estimation method for every activity is proposed based on the degree of fuzziness. The corresponding fuzzy activity duration time plot is also developed in a new fuzzy Gantt chart. The proposed model can provide a reasonable fuzzy finish time estimation for every activity, while most scheduling methods only provide the finish time of the entire project. Compared to existing models, this time estimation model and its corresponding Gantt chart are predicted to have higher reliability and practical application in project management and scheduling.

New concepts for activity float in resource-constrained project management

The concepts of float and critical path are central to analyzing activity networks in project management. In resource-constrained projects, schedule multiplicity makes it difficult to calculate float and identify critical activities accurately. In this work, new concepts of float and critical activity are developed to ascertain critical activities more precisely without reference to activity start and end times in specific schedules. The notions of float, group float, float set, negative float and zero critical activity are introduced, which the project manager can use to deal more effectively with critical activities, duration uncertainty, activity buffering, and resource allocation than the currently available tools in literature. For practical implementation, algorithms are provided and tested to calculate the new measures on the PSPLIB benchmark instances, specifically the J30, J60 and J120 test sets, for the resource constrained project management, illustrating the effectiveness of the proposed concepts in helping to identify flexibility in scheduling activities.

Split-dose bowel preparation for colonoscopy and residual gastric fluid volume: an observational study

Split-dose bowel preparations for colonoscopy are more effective and better tolerated than preparations given entirely the day or evening before the procedure; however, some resistance to split-dose preparation stems from concerns about an increased risk of aspiration with same-day preparation. We sought to evaluate residual gastric volumes in patients after split-dose bowel preparations. Prospective measurement of residual gastric volumes in patients undergoing same-day EGD and colonoscopy after split-dose bowel preparations, patients undergoing EGD alone, or patients undergoing EGD and colonoscopy after bowel preparation given entirely the evening before the procedure. Tertiary care hospital-based endoscopy unit. This study involved 712 patients, including 254 in the split-dose bowel preparation group, 411 in the EGD-only group, and 47 in the evening-before-procedure bowel preparation group. Measurement of residual gastric volume before endoscopic procedures. Residual gastric volume. The mean residual gastric volume in patients receiving split-dose bowel preparation (19.7 mL) was higher than in patients undergoing EGD alone (14.6 mL) but not different from that in patients receiving bowel preparation the evening before the procedure (20.2 mL). Within the split-dose preparation group, there was no association between the interval from last actual fluid ingestion and procedure start time and the residual gastric volume. The range of residual gastric volumes between study arms was similar. Nonrandomized study. The number of inpatients undergoing split-dose bowel preparation was small. These data support the safety of split-dose bowel preparation for outpatients undergoing colonoscopy.

Maximizing the net present value of a project under uncertainty

We address the maximization of a project’s expected net present value when the activity durations and cash flows are described by a discrete set of alternative scenarios with associated occurrence probabilities. In this setting, the choice of scenario-independent activity start times frequently leads to infeasible schedules or severe losses in revenues. We suggest to determine an optimal target processing time policy for the project activities instead. Such a policy prescribes an activity to be started as early as possible in the realized scenario, but never before its (scenario-independent) target processing time. We formulate the resulting model as a global optimization problem and present a branch-and-bound algorithm for its solution. Extensive numerical results illustrate the suitability of the proposed policy class and the runtime behavior of the algorithm.

Predetermined intervals for start times of activities in the stochastic project scheduling problem

This paper proposes a new methodology to schedule activities in projects with stochastic activity durations. The main idea is to determine for each activity an interval in which the activity is allowed to start its processing. Deviations from these intervals result in penalty costs. We employ the Cross-Entropy methodology to set the intervals so as to minimize the sum of the expected penalty costs. The paper describes the implementation of the method, compares its results to other heuristic methods and provides some insights towards actual applications.

Optimizing the Arrival, Waiting, and NPO Times of Children on the Day of Pediatric Endoscopy Procedures

Research in predictive variability of operating room (OR) times has been performed using data from multidisciplinary, tertiary hospitals with mostly adult patients. In this article, we discuss case-duration prediction for children receiving general anesthesia for endoscopy. We critique which of the several types of OR management decisions dependent on accuracy of prediction are relevant to series (lists) of brief pediatric anesthetics. OR information system data were obtained for all children (aged 18 years and younger) undergoing a gastroenterology procedure with an anesthesiologist over 21 months. Summaries of data were used for a qualitative, systematic review of prior studies to learn which apply to brief pediatric cases. Patient arrival times were changed to be based on the statistical method relating actual and scheduled start times (Wachtel and Dexter, Anesth Analg 2007;105:127-40). Even perfect case-duration prediction would not affect whether a brief case was performed on a certain date and/or in a certain OR. There was no evidence of usefulness in calculating the probability that one case would last longer than another or in resequencing cases to influence postanesthesia care unit staffing or patient waiting from scheduled start times. The only decision for which the accuracy of case-duration prediction mattered was for the shortest time that preceding cases in the OR may take. Knowledge of the preceding procedures in the OR was not useful for that purpose because there were hundreds of combinations of preceding procedures and some cases cancelled. Instead, patient ready times were chosen based on 5% lower prediction bounds for ratios of actual to scheduled OR times. The approach was useful based on a 30% reduction in patient waiting times from scheduled start times with corresponding expected reductions in average and peak numbers of patients in the holding area. For brief pediatric OR anesthetics, predictive variability of case durations matters principally to the extent that it affects appropriate patient ready times. Such times should not be chosen by having patients start fasting, arrive, and be ready fixed numbers of hours before their scheduled start times.

AN OPTIMAL METHOD FOR SCHEDULING CONSTRUCTION PROJECTS INCLUDING REPETITIVE ACTIVITIES IN MANY UNITS

This paper presents an optimal method for scheduling construction projects including many repetitive activities in many similar units (e.g., high-rise bridges...). The objective of scheduling is to minimize the project duration. This method considers many types of activities with different characteristics (activities must be performed continuously to insure the continuity in their performances, or activities can allow interruptions in their performances) to generate a satisfactory schedule for project managers. This method uses a new scheduling algorithm to find the optimal start and finish times of activities, so that the project duration is minimized. A well-known example is used as an illustration to show advantages of this method to other methods.

Multiday Multiagent Model of Travel Behavior with Activity Scheduling

A 7-day multiagent model of travel demand is presented. Multiday modeling has several strong points and expands the applicability of travel demand models. It allows for incorporating the interrelationship of individual budgets and travel behavior, and the model output provides high flexibility for the further use of the data. Multiday models allow simulation of individual mode use over time and identification of mode clienteles. The challenge of multiday modeling is the realistic representation of behavioral variability and stability and dealing with a large number of possible combinations when generating activity schedules. The presented activity generation approach has two steps: ( a) deriving agendas of intended activities from observed activity schedules and assigning the agendas to the agents in the model and ( b) transforming these agendas to feasible activity schedules with specific activity start times and activity destinations by using a greedy algorithm. This activity generation module was incorporated in a 7-day travel demand model. The model was applied for predicting changes in mode use in the German city of Erlangen caused by demographic development and growth in car ownership within the next decade.

Role-oriented process-driven enterprise cooperative work using the combined rule scheduling strategies

The key to enterprise process simulation and process enactment is to implement enterprise process cooperative schedule, i.e., how to control the execution order of the scheduled activities according to cooperative behavior rules under resource constraints. This paper proposes a dynamic PERT/CPM approach using a compound number, and discusses its applications to dynamic enterprise process scheduling for Computer Supported Cooperative Work (CSCW). By using the compound number, activity's duration, the earliest start time, and the latest start time of activities in a process model can be defined and calculated effectively to facilitate the enterprise process flexible scheduling and process forecast during process enactment. A framework to role-oriented process-driven enterprise cooperative work is proposed, some schedule strategies and the algorithm implementation are discussed, as well as the process-driven enterprise application integration.

Study on Motor Learning of Sternocleidomastoid Muscles during Ballistic Voluntary Opening

Neck pain is one of the main symptoms of temporomandibular disorder. Muscle activity of the sternocleidomastoid muscle during occlusion has been clarified in recent years. We reported that when healthy individuals were instructed to chew rapidly, the activity of the sternocleidomastoid muscle responded to activity of the masseter muscle, however, during voluntary jaw opening, activity of the sternocleidomastoid muscle did not respond, but worked actively due to motor programming. The objective of the present study was to investigate the learning effects of repetitive training, that is, changes in activity mode of the neuromuscular system. The sternocleidomastoid and the anterior belly of digastric muscles in 8 healthy male adults were analyzed. In response to acoustic stimulation, each subject was instructed to open their mouth as quickly and widely as possible a total of 30 times with a break between measurements. EMG-reaction times (RT) of the sternocleidomastoid and anterior belly of digastric muscles were measured, and the length of time from the start of EMG activity of agonist to the start of actual movement was measured. In all subjects, at first measurement, EMGRT of the sternocleidomastoid muscle did not precede that of the anterior belly of digastric muscle. With each measurement, the difference in EMG-RT between the sternocleidomastoid and the anterior belly of digastric muscles decreased, and in 6 of the 8 subjects, EMG-RT of the sternocleidomastoid muscle preceded that of the anterior belly of digastric muscle. Repetitive task movement alters the start times of muscular activities, and from the perspective of EMG kinesiology, motor learning effects were confirmed with maximum ballistic voluntary jaw opening.

Critical Path Scheduling under Resource Calendar Constraints

Resource calendars specify nonworking days of driving resources involved in construction projects. As part of the resource availability constraints in critical path method (CPM) scheduling, resource calendars may postpone activity start time, extend activity duration, and hence prolong the total project duration. Ultimately, resource calendars bring about changes to the critical path identification. Research has yet to address how to incorporate the effects of multiple resource calendars on the total float determination. In this research, the popular P3 software is used as a tool for investigating the current practice of CPM scheduling under resource limit and calendar constraints. We assess P3’s advanced resource scheduling functions (including resource leveling and resource calendars) and identify P3’s potential errors in total float determination. Further, we propose a new method based on the forward pass analysis alone for accurately evaluating activity total float subject to resource calendar constra...

A Large Margin Algorithm for Speech-to-Phoneme and Music-to-Score Alignment

We describe and analyze a discriminative algorithm for learning to align an audio signal with a given sequence of events that tag the signal. We demonstrate the applicability of our method for the tasks of speech-to-phoneme alignment (ldquoforced alignmentrdquo) and music-to-score alignment. In the first alignment task, the events that tag the speech signal are phonemes while in the music alignment task, the events are musical notes. Our goal is to learn an alignment function whose input is an audio signal along with its accompanying event sequence and its output is a timing sequence representing the actual start time of each event in the audio signal. Generalizing the notion of separation with a margin used in support vector machines for binary classification, we cast the learning task as the problem of finding a vector in an abstract inner-product space. To do so, we devise a mapping of the input signal and the event sequence along with any possible timing sequence into an abstract vector space. Each possible timing sequence therefore corresponds to an instance vector and the predicted timing sequence is the one whose projection onto the learned prediction vector is maximal. We set the prediction vector to be the solution of a minimization problem with a large set of constraints. Each constraint enforces a gap between the projection of the correct target timing sequence and the projection of an alternative, incorrect, timing sequence onto the vector. Though the number of constraints is very large, we describe a simple iterative algorithm for efficiently learning the vector and analyze the formal properties of the resulting learning algorithm. We report experimental results comparing the proposed algorithm to previous studies on speech-to-phoneme and music-to-score alignment, which use hidden Markov models. The results obtained in our experiments using the discriminative alignment algorithm are comparable to results of state-of-the-art systems.

Fuzzy Activity Network Method for Project Scheduling Under Resource Constraints

In this article, a fuzzy activity network method is developed for project scheduling under resource constraints. Trapezoidal fuzzy numbers are used for estimating uncertain durations of activities, and then these fuzzy numbers are replaced by suitable crisp durations for project scheduling under resource constraints. In the next step, the critical chain is identified for determining the project duration, and uncertainties associated with activities are addressed by using feeding/project buffers to protect the project schedule from disturbances. For minimizing project duration, the proposed method considers both the suitable crisp durations and the start times of activities as decision variables. Hence, a new procedure based on genetic algorithm and priority heuristics is also developed for efficiently determining these decision variables. Furthermore, the method also considers selecting the best possible relationships between activities to minimize project duration. The proposed method using buffers makes it possible to improve project scheduling under resource constraints.

A Simple Method for Deciding When Patients Should Be Ready on the Day of Surgery Without Procedure-Specific Data

Deciding when patients should arrive for same-day-admission or ambulatory surgery is a problem at many hospitals and surgery centers. Although staff can often start cases earlier than scheduled, the potential start times are not known when each case is scheduled. Patient availability must therefore be balanced against patient waiting times and fasting times. Knowing the earliest time that a case might begin, given its scheduled start time, provides a rational basis for telling patients when to report for surgery and when to refrain from eating or drinking before their procedure. We describe and validate a simple method for determining the earliest possible start time for a case, with only a 5% probability that staff would be able to start the case even earlier. Calculations use nonparametric methods to determine the 0.05 lower prediction bound for the start time of a case, using historical values for the scheduled and actual start times of cases performed by the same surgical suite/surgical service/day of the week combination as the case of interest. Information is not needed regarding the preceding cases performed in the same operating room. No patient or surgeon identifiable information is used. We use results from earlier studies to provide a derivation and theoretical justification for these methods. New data confirm the validity of the results obtained and show that the required calculations are easy to implement. Individualized patient instructions can be accessed via a public website without disclosing confidential information. We have developed a simple method for determining when patients should be ready on the day of surgery based on the start times of historical cases performed by the same surgical suite/surgical service/day of the week combination as the case of interest.

Ｂｏｌｕｓ Ｔｒａｃｋｉｎｇ法を用いたＣｏｒｏｎａｒｙ Ａｎｇｉｏ ＣＴにおける造影剤濃染濃度を捉えた撮影タイミングの検討

Negative product value for coronary artery disease is 98% to 99%. Therefore, the number of unnecessary cardiac catheterization procedures is reduced as the usefulness of CT systems for examination of the coronary arteries improves. In the bolus-tracking method, in which an ROI is placed in the ascending aorta to trigger scanning, scanning may not be performed at the optimal time of contrast enhancement depending on the patient. In addition to identifying the causes of this problem, we have developed a new method in which ROIs are placed in the right ventricle and left atrium to trigger scanning when the concentrations of contrast medium in the right ventricle and left atrium become equal. The two methods were then compared and evaluated. In the scan method, in which an ROI is placed in the ascending aorta, the reason for non-optimal scan timing is considered to be that the time required for contrast medium injected via an antecubital vein to reach the heart varies depending on the individual patient(approximately 3 times the variation of our method)followed by a delay of approximately 5 seconds between the scan trigger time and the actual scan start time. In the scan method in which scanning is triggered when the concentrations of contrast medium in the right ventricle and left atrium become equal, scanning can be performed at the time of peak enhancement regardless of differences in the time required for the injected contrast medium to reach the target region or differences in the injection rate, demonstrating the usefulness of this method.

A GA-based household scheduler

One way of making activity-based travel analysis operational for transport planning is multi-agent micro-simulation. Modelling activity and trip generation based on individual and social characteristics are central steps in this method. The model presented here generates complete daily activity schedules based on the structure of a household and its members’ activity calendars. The model assumes that the household is another basic decision-making unit for travel demand aside from individual mobility needs. Results of the model are schedules containing complete information about activity type and sequence, locations, and means of transportation, as well as activity start times and durations. The generated schedules are the outcome of a probabilistic optimisation using genetic algorithms. This iterative method improves solutions found in a random search according to the specification of a fitness criterion, which equals utility here. It contains behavioural assumptions about individuals as well as the household level. Individual utility is derived from the number of activities and their respective durations. It is reduced by costs of travelling and penalties for late, respectively early arrival. The household level is represented directly by the utility of joint activities, and indirectly by allocation of activities and means of transportation to household members. The paper presents initial tests with a three-person household, detailing resulting schedules, and discussing run-time experiences. A sensitivity analysis of the joint utility parameter impact is also included.