In this paper, we propose a procedure, based on statistical design of experiments and gradient descent, that finds effective settings for parameters found in heuristics. We develop our procedure using four experiments. We use our procedure and a small subset of problems to find parameter settings for two new vehicle routing heuristics. We then set the parameters of each heuristic and solve 19 capacity-constrained and 15 capacity-constrained and route-length-constrained vehicle routing problems ranging in size from 50 to 483 customers. We conclude that our procedure is an effective method that deserves serious consideration by both researchers and operations research practitioners. Key Words: statistical design of experiments, heuristics, vehicle routing 1.

Many formalisms and solution methods exist for performance and dependability modeling. However, different formalisms have different advantages and strengths, and no one formalism is universally used. The Möbius

Software quality can be defined as the customer’s perception of how a system works. Inspection is a method to control the quality throughout the development cycle. Reading techniques applied to inspections help reviewers to stay focused on the important parts of an artefact when inspecting. However, many reading techniques focus on finding as many faults as possible, regardless of their importance. Usage-based reading helps reviewers to focus on the most important part of an software artefact from a user’s point of view. This paper is an extended abstract of a technical report describing an experiment, which compares usagebased and checklist-based reading. The results show that reviewers applying usage-based reading are more efficient and effective in detecting the most critical faults from a user’s point of view than reviewers using checklist-based reading. Usage-based reading may be preferable to use for software organisations utilising or will start utilising use cases in their software development. 1.

roadmap construction for path planning. The novel feature of the planner is that it uses a powerful local planner to produce highly connected roadmaps and path optimization to maintain the rapid query processing by a fast local operator. While most previous approaches obtain good roadmaps by advanced sampling methods, the presented approach concentrates on the method used to connect the samples. Empirical results show that the new approach outperforms the more traditional approach of using fast local planners in capability to produce roadmaps with only few connected components. Statistical analysis is used to identify features important for the efficiency of the local planners.

Processor architects have a challenging task of evaluating a large design space consisting of several interacting parameters and optimizations. In order to assist architects in making crucial design decisions, we build linear regression models that relate processor performance to micro-architectural parameters, using simulation based experiments. We obtain good approximate models using an iterative process in which Akaike’s information criteria is used to extract a good linear model from a small set of simulations, and limited further simulation is guided by the model using D-optimal experimental designs. The iterative process is repeated until desired error bounds are achieved. We used this procedure to establish the relationship of the CPI performance response to 26 key micro-architectural parameters using a detailed cycle-by-cycle superscalar processor simulator. The resulting models provide a significance ordering on all micro-architectural parameters and their interactions, and explain the performance variations of micro-architectural techniques. 1.

Abstract not found

In the early stages of design of complex systems, it is necessary to explore the design space to determine a suitable range for specifications and identify feasible starting points for design. Thus, a robust concept exploration method have been developed to improve the efficiency and effectiveness of the process of identifying suitable starting points for the design of complex systems. Using this method, quality concepts (robustness) are introduced into the choice of the initial specifications for design. The Concept exploration is implemented by integrating the Response Surface Method, robust design techniques and the compromise Decision Support Problem. The proposed approach is demonstrated to determining top-level specifications for airframe geometry and the propulsion system for the High Speed Civil Transport aircraft. The focus in this paper is on illustrating the approach rather than on the results per se. Word Count: 6986. Key words: Concept exploration, robust design, specifi...

Regression testing is an expensive testing process used to validate software following modi cations. The cost-e ectiveness of regression testing techniques varies with characteristics of test suites. One such characteristic, test suite granularity, involves the way in which test inputs are grouped into test cases within a test suite. Various cost-bene ts tradeo s have been attributed to choices of test suite granularity, but almost no research has formally examined these tradeo s. To address this lack, we conducted several controlled experiments, examining the e ects of test suite granularity on the costs and bene ts of several regression testing methodologies across six releases of two non-trivial software systems. Our results expose essential tradeo s to consider when designing test suites for use in regression testing evolving systems.

The optimization of complex real-world problems might benefit from well tuned algorithm's parameters. We propose a methodology that performs this tuning in an effective and efficient algorithmical manner. This approach combines methods from statistical design of experiments, regression analysis, design and analysis of computer experiments methods, and tree-based regression. It can also be applied to analyze the influence of different operators or to compare the performance of different algorithms. An evolution strategy and a simulated annealing algorithm that optimize an elevator supervisory group controller system are used to demonstrate the applicability of our approach to real-world optimization problems.

this paper can be stated as follows: A set V = f0; 1; : : : ; n; n+1g of activities has to be processed. Fictitious activity 0 and n+1 correspond to the "project start" and to the "project end", respectively. The activities use renewable resources and consume nonrenewable resources. The sets of renewable and nonrenewable resources are denoted by K