25 research outputs found
SOLVING SCHEDULING PROBLEMS AS THE PUZZLE GAMES USING CONSTRAINT PROGRAMMING
No full textConstraint programming (CP) is one of the most effective techniques for solving practical operational problems. The outstanding feature of the method is a set of constraints affecting a solution of a problem can be imposed without a need to explicitly defining a linear relation among variables, i.e. an equation. Nevertheless, the challenge of paramount importance in using this technique is how to present the operational problem in a solvable Constraint Satisfaction Problem (CSP) model. The problem modelling is problem independent and could be an exhaustive task at the beginning stage of problem solving, particularly when the problem is a real-world practical problem. This paper investigates the application of a simple grid puzzle game when a player attempts to solve practical scheduling problems. The examination scheduling and logistic fleet scheduling are presented as operational games. The game‘s rules are set up based on the operational practice. CP is then applied to solve the defined puzzle and the results show the success of the proposed method. The benefit of using a grid puzzle as the model is that the method can amplify the simplicity of CP in solving practical problems
RFID enabled constraint based scheduling for transport logistics
No full textThis research aims to develop a realistic solution to enhance the efficiency of a transport logistics operation. The case study in this research is one of the largest agricultural suppliers in Northern Thailand. The cost of logistics in Thailand is relatively high compared to other countries, Le. 11% of Gross Domestic Product (GOP) in 2007, and is particularly high in agricultural sector. The focus of the study is to enhance and improve transportation activities which typically account for the largest cost in logistics. The research is entitled 'RFID enabled constraint based scheduling for transport logistics' The dissertation studies two important research components: 1) the data acquisition using Radio Frequency Identification Technology (RHO) for monitoring vehicles in a depot and 2) the scheduling by solving Constraint Satisfaction Optimisation Problem (CSOP) using Constraint Programming (CP). The scheduling problem of the re search is to compose and schedule a fleet in which both private and subcontracting (outsourcing) vehicles are available, but to minimise the use of subcontractors. Several contributions from this study can be identified at each stage of the study ranging from extensively reviewing the literature, field studies, developing the RFIO prototype system for vehicle tracking, modelling and solving the defined scheduling problems using Constraint Programming, developing a RFIO·CP based real time scheduling, and validating the proposed methods. A numbe r of validations are also carried out throughout the research. For instance, laboratory based experiments were conducted to measure the performance of the developed RFIO tracking system in different configurations. Scenario tests were used to test the correctness of the proposed CP·based scheduling system, and structure interviews were used to collect feedbacks on the developed prototype from the case study company.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Solving Scheduling Problems as the Puzzle Games Using Constraint Programming
No full textConstraint programming (CP) is one of the most effective techniques for solving practical operational problems. The outstanding feature of the method is a set of constraints affecting a solution of a problem can be imposed without a need to explicitly defining a linear relation among variables, i.e. an equation. Nevertheless, the challenge of paramount importance in using this technique is how to present the operational problem in a solvable Constraint Satisfaction Problem (CSP) model. The problem modelling is problem independent and could be an exhaustive task at the beginning stage of problem solving, particularly when the problem is a real-world practical problem. This paper investigates the application of a simple grid puzzle game when a player attempts to solve practical scheduling problems. The examination scheduling and logistic fleet scheduling are presented as operational games. The game‘s rules are set up based on the operational practice. CP is then applied to solve the defined puzzle and the results show the success of the proposed method. The benefit of using a grid puzzle as the model is that the method can amplify the simplicity of CP in solving practical problems
A technical solution to improve the red cab for touring in Chiang Mai: Chinese tourists' perspective
No full text
Feasibility study of using mobile application to support triage and diagnosis clinical decisions for pediatricians: User-centered design approach
No full textBackground While there is some evidence in the literature demonstrating success in using a triage software application in ED, none of the solution was developed specifically to support a holistic decision of pediatricians in triage and diagnosis purposes to initiate the first treatment properly. To explore the usefulness and possibility of employing a digital-based solution to enhance clinician performance, the mobile application was developed and then assessed in different perspectives. Objective The primary objective of this study is to contribute implementation practice of an application to support pediatric triage and diagnoses. The secondary objective is to present the results of the preliminary evaluation of the application. Methods The application called Pedicmeter was developed. Formative tests with revisions were applied throughout the development phase. A number of summative extensive evaluations were also conducted to investigate the efficacy of the proposed method. The evaluation focused on measuring the ability of an application to support a pediatric staff’s decision to determine an overall severity level and disease diagnosis. Finally, the user’s (clinician's) satisfaction of using the application was measured. Results The application Pedicmeter enables clinicians to make more accurate decisions in determining emergency level of pediatric patients by 6.66%. The application accurately diagnosed a disease with 73.08% accuracy and 66.67% accuracy for respiratory and infectious diseases, respectively. The diagnostic information that the application suggested shows that it does have an influence on a clinician’s diagnosis. Using the app showed improvements in diagnostic accuracy for asthma, croup, sepsis, but it showed a decrease in the accuracy of a clinician's decision for pneumonia. The benefit of the application that satisfies the pediatricians the most is the helpfulness of the features of the application (86%), while the least satisfying factor was the required number of inputs (63%). Conclusion The developed application conceptually shows a promising opportunity to enhance clinicians’ decisions from the pilot study. However, the study also reveals further tweaks are required and unveils challenging issues and the concerns of clinician users when use the application. Further research will be conducted to investigate and determine the limiting factors and specific issues revealed by this study. Longitudinal data collection and analysis also need to be conducted to investigate the clinical implications
