5,861 research outputs found
Shift Scheduling Optimization for PSU Library
Scheduling is important in any business as it creates an order and flow ensuring that all the tasks are covered at appropriate times. According to experts, scheduling determines the economics of a job, the quality of the team, and the skill-building and motivation of professionals doing the work. Therefore, it is essential to have optimized staff schedules to meet the requirements of staff availability, tasks coverage, shift equity and staff preferences. Though staff scheduling is of such prime importance, it is mostly implemented in traditional ways of manually creating spreadsheets and web calendars proving to be laborious and often leaving room for errors. Additionally, staff preferences are arbitrarily handled through this format which results in overstaffing /understaffing of resources. Our project is aimed at developing an optimization model of staff scheduling for the PSU library using linear programming and create a tool with open solver that reduces the surplus working hours of the staff in the library while maximizing the staff preferences. We expect our model to achieve better efficiency and flexibility than the traditional format of scheduling implemented by the library. Also, our model could have broader capabilities of implementation in different departments of the Portland State University
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Leveraging simulation practice in industry through use of desktop grid middleware
This chapter focuses on the collaborative use of computing resources to support decision making in industry. Through the use of middleware for desktop grid computing, the idle CPU cycles available on existing computing resources can be harvested and used for speeding-up the execution of applications that have “non-trivial” processing requirements. This chapter focuses on the desktop grid middleware BOINC and Condor, and discusses the integration of commercial simulation software together with free-to-download grid middleware so as to offer competitive advantage to organizations that opt for this technology. It is expected that the low-intervention integration approach presented in this chapter (meaning no changes to source code required) will appeal to both simulation practitioners (as simulations can be executed faster, which in turn would mean that more replications and optimization is possible in the same amount of time) and the management (as it can potentially increase the return on investment on existing resources)
A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning
Real world combinatorial optimization problems such as scheduling are
typically too complex to solve with exact methods. Additionally, the problems
often have to observe vaguely specified constraints of different importance,
the available data may be uncertain, and compromises between antagonistic
criteria may be necessary. We present a combination of approximate reasoning
based constraints and iterative optimization based heuristics that help to
model and solve such problems in a framework of C++ software libraries called
StarFLIP++. While initially developed to schedule continuous caster units in
steel plants, we present in this paper results from reusing the library
components in a shift scheduling system for the workforce of an industrial
production plant.Comment: 33 pages, 9 figures; for a project overview see
http://www.dbai.tuwien.ac.at/proj/StarFLIP
Decision support tool for Operations Management course and instructor scheduling
The goal of this project is develop a decision support tool that will assist the Operations Management Department at the University of Arkansas with scheduling courses and instructors for the upcoming academic year. The staff of the department dreads this time each year because it takes countless hours to complete the daunting task. Creating an abstract mathematical model will assist the department in scheduling the courses. The model will have the ability to optimize the schedule of the courses and instructors from a large number of variables and constraints that the department requires. An optimization software package can solve the problem based on the data for the upcoming year. The staff will be able to use a decision support tool to input the relevant data with ease, and run the optimization software package with little knowledge of how mathematical models work. The focus of this project will be creating an abstract class-scheduling mathematical model that will be easily solved through the creation of a decision support tool. The tool will optimize the schedule, and save the staff precious time that could be spent elsewhere
Microcomputers in City Hall: Case Studies of Their Uses and Effects
Microcomputers first appeared on the commercial marketplace in 1976. Since then, an estimated 40 million microcomputers have been sold and more are being sold each day. A survey conducted in 1982 found that 13 percent of American cities owned microcomputers and that 35 percent planned to buy one or more microcomputers within two years (Norris and Webb, 1984). A follow-up survey conducted three years later found that between 75 percent and 90 percent of city governments owned microcomputers (Scoggins, 1986)
Specification of vertical semantic consistency rules of UML class diagram refinement using logical approach
Unified Modelling Language (UML) is the most popular modelling language use for
software design in software development industries with a class diagram being the
most frequently use diagram. Despite the popularity of UML, it is being affected by
inconsistency problems of its diagrams at the same or different abstraction levels.
Inconsistency in UML is mostly caused by existence of various views on the same
system and sometimes leads to potentially conflicting system specifications. In
general, syntactic consistency can be automatically checked and therefore is
supported by current UML Computer-aided Software Engineering (CASE) tools.
Semantic consistency problems, unlike syntactic consistency problems, there exists
no specific method for specifying semantic consistency rules and constraints.
Therefore, this research has specified twenty-four abstraction rules of class‟s relation
semantic among any three related classes of a refined class diagram to semantically
equivalent relations of two of the classes using a logical approach. This research has
also formalized three vertical semantic consistency rules of a class diagram
refinement identified by previous researchers using a logical approach and a set of
formalized abstraction rules. The results were successfully evaluated using hotel
management system and passenger list system case studies and were found to be
reliable and efficient
Evaluation of Patient Throughput in an Outpatient Pediatric Hematology, Oncology, and Bone Marrow Transplant Clinic
Background: Outpatient oncology clinics are complex environments. The multi-step, sequential nature of oncology treatment contributes to delays. Prolonged wait time impacts patient compliance, satisfaction, and staff satisfaction.
Objectives: To assess throughput in the outpatient pediatric oncology clinic and explore staff’s assessment of throughput and their opinions of what might be improved.
Methods: Our descriptive-comparative study used retrospective reviews to measure four time intervals for 312 visits at our mid-Atlantic outpatient clinic. Patient and appointment factors were explored. Mean interval times were calculated and differences impacting throughput were analyzed using ANOVA. Prospective survey data were obtained from 22 clinic staff and themes were identified.
Results: The shortest interval was check-in to triage (18.49 ± 18.21 minutes) while the longest was from receiving laboratory results to treatment initiation (136.73 ± 77.98 minutes). Throughput was significantly shorter for appointments consisting of provider visit and laboratory studies only compared to visits involving infusions and blood product transfusions (p \u3c .001). Throughput for 8:00-10:00 a.m. appointments was significantly longer than 2:01-6:00 p.m. appointments (p = .013). Staff respondents reported throughput was suboptimal. Common problems identified were appointment noncompliance, laboratory workflow, triage and front desk bottlenecks, physician timeliness, fellow workflow, and “saving seats”.
Conclusions: Delays occurred at each clinic intersection but were significantly longer with early clinic appointments and infusion and transfusion visits. Staff highlighted problems at each clinic juncture and overarching problems that caused inefficiencies. We identified priority areas to be addressed via targeted interventions in a structured action plan to improve clinic efficiency and throughput
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