Meta-raps: Parameter Setting And New Applications

Recently meta-heuristics have become a popular solution methodology, in terms of both research and application, for solving combinatorial optimization problems. Meta-heuristic methods guide simple heuristics or priority rules designed to solve a particular problem. Meta-heuristics enhance these simple heuristics by using a higher level strategy. The advantage of using meta-heuristics over conventional optimization methods is meta-heuristics are able to find good (near optimal) solutions within a reasonable computation time. Investigating this line of research is justified because in most practical cases with medium to large scale problems, the use of meta-heuristics is necessary to be able to find a solution in a reasonable time. The specific meta-heuristic studied in this research is, Meta-RaPS; Meta-heuristic for Randomized Priority Search which is developed by DePuy and Whitehouse in 2001. Meta-RaPS is a generic, high level strategy used to modify greedy algorithms based on the insertion of a random element (Moraga, 2002). To date, Meta-RaPS had been applied to different types of combinatorial optimization problems and achieved comparable solution performance to other meta-heuristic techniques. The specific problem studied in this dissertation is parameter setting of Meta-RaPS. The topic of parameter setting for meta-heuristics has not been extensively studied in the literature. Although the parameter setting method devised in this dissertation is used primarily on Meta-RaPS, it is applicable to any meta-heuristic\u27s parameter setting problem. This dissertation not only enhances the power of Meta-RaPS by parameter tuning but also it introduces a robust parameter selection technique with wide-spread utility for many meta-heuristics. Because the distribution of solution values generated by meta-heuristics for combinatorial optimization problems is not normal, the current parameter setting techniques which employ a parametric approach based on the assumption of normality may not be appropriate. The proposed method is Non-parametric Based Genetic Algorithms. Based on statistical tests, the Non-parametric Based Genetic Algorithms (NPGA) is able to enhance the solution quality of Meta-RaPS more than any other parameter setting procedures benchmarked in this research. NPGA sets the best parameter settings, of all the methods studied, for 38 of the 41 Early/Tardy Single Machine Scheduling with Common Due Date and Sequence-Dependent Setup Time (ETP) problems and 50 of the 54 0-1 Multidimensional Knapsack Problems (0-1 MKP). In addition to the parameter setting procedure discussed, this dissertation provides two Meta-RaPS combinatorial optimization problem applications, the 0-1 MKP, and the ETP. For the ETP problem, the Meta-RaPS application in this dissertation currently gives the best meta-heuristic solution performance so far in the literature for common ETP test sets. For the large ETP test set, Meta-RaPS provided better solution performance than Simulated Annealing (SA) for 55 of the 60 problems. For the small test set, in all four different small problem sets, the Meta-RaPS solution performance outperformed exiting algorithms in terms of average percent deviation from the optimal solution value. For the 0-1 MKP, the present Meta-RaPS application performs better than the earlier Meta-RaPS applications by other researchers on this problem. The Meta-RaPS 0-1 MKP application presented here has better solution quality than the existing Meta-RaPS application (Moraga, 2005) found in the literature. Meta-RaPS gives 0.75% average percent deviation, from the best known solutions, for the 270 0-1 MKP test problems

Production Scheduling for OCS Blount Corporation

This project was undertaken to find an optimal number of products and the type of products to produce in one month. A problem formulation that often lends itself to solutions usmg Linear Programming techniques are situations including productions scheduling and resource allocations in a manufacturing line. A saw chain manufacturing company was examined in terms of production scheduling problem. As a reference for a realistic set of data related to this specific company and industry was analyzed during this project. The problem definition and formulation processes turned around finding an optimal solution for production schedule based on constraints of plant capacity. The steps that we pursued during this project are determination of model, constructing the objective function, exploring the parameters of the various processes involved in manufacturing guide bars, and identifying limits and constraints on that process. Having accomplished these steps, we transformed our model to the software package that we learned during our course. We used Solver software package to find an optimal solution to our model. Finally after running our model we came up with following solution, which says that production amounts for 16 inch, 14 inch and 12 inch respectively 27,142 ; 10,000 and 4,000. On the other selling amounts are for that order are 26,942; 9,710 and 4,120. We cannot sell as much as the demand from the market. There are some binding constraints which prevent us from meeting demand fully

Formal Project Management at JACS, Inc.

JACS, Inc is a rapidly growing software company that is suffering from the excess fat of a large organization. When JACS was a small company of 150 employees, it was able to work closely with its customers to and adapt quickly to their changing needs. Now as a larger company, it is having a difficult time being responsive to customer needs. This case study discusses the steps that JACS went through to move from a traditionally functional organization to a project oriented organization. A Project Management team was brought in to develop a strategy for implementing formal project management. A SWOT (strengths, weaknesses, opportunities and threats) analysis was done by the team and several strategies were considered. The preferred strategy was recommended along with an implementation plan. This plan was broken out into 3 different phases with short-term goals, mid-term goals, and long-term goals. JACS is now 3 years into this implementation plan. Some of the benefits and challenges that were experienced while implementing this strategy are discussed. In addition to that, JASC\u27s future plans, as it moves forward to reach excellence in project management, are discussed

Nonparametric Comparison of Two Dynamic Parameter Setting Methods in a Meta-Heuristic Approach

Meta-heuristics are commonly used to solve combinatorial problems in practice. Many approaches provide very good quality solutions in a short amount of computational time; however most meta-heuristics use parameters to tune the performance of the meta-heuristic for particular problems and the selection of these parameters before solving the problem can require much time. This paper investigates the problem of setting parameters using a typical meta-heuristic called Meta-RaPS (Metaheuristic for Randomized Priority Search.). Meta-RaPS is a promising meta-heuristic optimization method that has been applied to different types of combinatorial optimization problems and achieved very good performance compared to other meta-heuristic techniques. To solve a combinatorial problem, Meta-RaPS uses two well-defined stages at each iteration: construction and local search. After a number of iterations, the best solution is reported. Meta-RaPS performance depends on the fine tuning of two main parameters, priority percentage and restriction percentage, which are used during the construction stage. This paper presents two different dynamic parameter setting methods for Meta-RaPS. These dynamic parameter setting approaches tune the parameters while a solution is being found. To compare these two approaches, nonparametric statistic approaches are utilized since the solutions are not normally distributed. Results from both these dynamic parameter setting methods are reported

Term Project: Statistical Analysis of Baby Birth Patterns in Oregon (1985-2000)

The aim of this project is to get familiar with statistical analysis by the use of reallife data. The data used in this report is the number of baby births between 1985 and 2000 in Oregon. The requirements of this project is clearly defined by steps of 8 procedures that belong to 2 parts

A Metaheuristic For The Early/Tardy Single Machine Scheduling Problem

This paper addresses the Early/Tardy Single Machine Scheduling Problem with Common Due Date and Sequence-Dependent Setup Times (ETP). The objective of this problem is to minimize the total amount of earliness and tardiness of jobs that are assigned to a single machine. ETP in this research is solved by Meta-RaPS (Meta-heuristic for Randomized Priority Search) which is a typical multi-start meta-heuristic. Results for several ETP test problems show the Meta-RaPS ETP method produces high quality solutions in reasonable computation time when compared to other ETP techniques found in the literature

Solving The 0-1 Multidimensional Knapsack Problem

This paper presents a meta-heuristic solution approach, Meta-RaPS, to 0-1 Multidimensional Knapsack Problem (0-1 MKP). Meta-RaPS (Meta-heuristic for Randomized Priority Search) constructs a feasible solution at each iteration through priority rules used in a randomized fashion to avoid local optimum. After the construction phase, Meta-RaPS improves the solution using a local search technique. The Meta-RaPS 0-1 MKP approach developed herein is tested using a well-known test set of 0-1 MKP problems from the OR-Library. The Meta-RaPS 0-1 MKP results are competitive with the literature findings in terms of time and solution quality

Nonparametric Comparison Of Two Dynamic Parameter Setting Methods In A Meta-Heuristic Approach

The use of meta-heuristics is very common when solving a combinatorial problem in practice. Some approaches provide very good quality solutions in a short amount of computational time, however the parameters must be set before solving the problem which could require much time. This paper investigates the problem of setting parameters using a typical meta-heuristic called Meta-RaPS (Metaheuristic for Randomized Priority Search.). Meta-RaPS is a promising meta-heuristic optimization method that has been applied to different types of combinatorial optimization problems and achieved very good performance compared to other meta-heuristic techniques. To solve a problem, Meta-RaPS uses two well-defined stages at each iteration: construction and local search. After a number of iterations, the best solution is reported. Meta-RaPS performance depends on the fine tuning of two parameters: the priority percentage and restriction percentage, which are used during the construction stage. This paper presents two different dynamic parameter setting methods to set Meta-RaPS parameters while at the same time a solution is being found. To compare these two approaches, nonparametric statistic approaches are utilized since the distribution of solutions is not normal. Results from both these dynamic parameter setting methods are reported

Development of CD Recordable

Since its launch in early 80\u27s, compact disc has proved itself to be one of the disruptive technologies of the decade. CD has virtually replaced the phonograph record and CD-ROM has help blaze the trail for the information era. Also, incremental innovations based on CD technology continuously emerge and CD-R is one of the most successful of these. CD-R technology was originally developed to support the manufacturing process of CDs. As the technology became more sophisticated, affordable, and user-friendly, the CD-R drive has become a standard tool for the average PC user. The development ofCD-R technology is a classic case of technology management; it faced different challenges and issues as it moved up the technology Scurve. A review of the success ofCD-R technology illustrates a few critical issues in technology management: Cross platform compatibility and standards: the ISO 9660 and the Frankfurt Format Combined force of technology push and market pull: the first generation CD-R technology and the need of higher capacity media of average users Affordability: commodity pricing of the CD-R disc Continuous performance improvements: Reading and writing speed, burn proof technology Advancements of supporting technologies: CD recording software, IDE interface, USB, and Fire Wire, etc

The Removable Data Storage Market

This analysis is the result of a desire to examine the market strategies at work in the Removable Data Storage Market. Our analysis takes a close look at various optical data storage technologies, magnetic hard disk drives, and silicon based storage technologies as well as the emerging long-term data storage technology alternatives. Each group is compared according to its segment. The market forces are analyzed with an emphasis on the strategies used by the market leaders in each segment of the market. The Critical Issues at work in the current market, along with the Key Success Factors of the leaders in the market are identified. From analysis of network effects, switching costs and lock in, first mover advantage, penetration prices and backward compatibility, it is shown that network effects and first mover advantage appear to have the most effect on this market. Research for this analysis was primarily complied using web-based, qualitative information gathered from sources like periodicals, articles and web-sites. Moreover, literature review has been made during this project to fully understand the market and its characteristics