18 research outputs found
AMCIS 2002 Panels and Workshops II: Spreadsheet-Based DSS Curriculum Issues
When challenged to justify the value of information systems (IS) research, decision support systems (DSS) is usually cited as one the most compelling examples of where IS research made the transition successfully from theoretical academic journals into the real-world . In light of this assessment, it is somewhat surprising that offerings of DSS courses waned over the years. This paper identifies several possible reasons for the decline in DSS course offerings and suggests innovative approaches using spreadsheets for breathing new-life into this cornerstone of the IS field
Spreadsheet modeling and decision analysis : a practical introduction to management science, 2nd.ed./ Ragsdale
x, p. 742: ill.; 26 c
Spreadsheet modeling and decision analysis : a practical introduction to management science, 2nd.ed./ Ragsdale
x, 742 hal.: ill.; 26 cm
Spreadsheet modeling and decision analysis : a practical introduction to management science, 2nd.ed./ Ragsdale
x, 742 hal.: ill.; 26 cm
A new approach to solving the multiple traveling salesperson problem using genetic algorithms
On modeling time series data using spreadsheets
Linear regression analysis has long been used to estimate the parameters of various types of times series (TS) models. In some cases, the application of traditional regression-based techniques to TS data does not produce the optimal values of the parameters being estimated. The nonlinear optimization tool (known as Solver) built into today's electronic spreadsheets can alleviate these estimation problems as well as simplify the process of modeling many types of TS problems. This paper presents two examples of TS problems where Solver performs better than regression-based TS techniques. It also encourages educators to reevaluate these and other traditional TS techniques in light of Solver's capabilities.Time series Regression Spreadsheets Education
Quality inspection scheduling for multi-unit service enterprises
The traveling salesman problem is a classic NP-hard problem used to model many production and scheduling problems. The problem becomes even more difficult when additional salesmen are added to create a multiple traveling salesman problem (MTSP). We consider a variation of this problem where one salesman visits a given set of cities in a series of short trips. This variation is faced by numerous franchise companies that use quality control inspectors to ensure properties are maintaining acceptable facility and service levels. We model an actual franchised hotel chain using traveling quality inspectors to demonstrate the technique. The model is solved using a commercially available genetic algorithm (GA) tool as well as a custom GA program. The custom GA is proven to be an effective method of solving the proposed model.Genetic algorithms Scheduling Traveling salesman