SOLUTION SPACE SMOOTHING FOR VLSI MODULE PLACEMENT: A COMPUTATIONAL STUDY

AbstractThis paper presents the results of computational experiments aimed at studying the effect of experience on design teams’ exploration of problem-solution space. An agent-based model of a design team was developed and its capability to match theoretically-based predictions is tested. Hypotheses that (1) experienced teams need less time to find a solution and that (2) in comparison to the inexperienced teams, experienced teams spend more time exploring the solution-space than the problem-space, were tested. The results provided support for both of the hypotheses, demonstrating the impact of learning and experience on the exploration patterns in problem and solution space, and verifying the system's capability to produce the reliable results.

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Layout Design of Parking Lots with Mathematical Programming

Transportation Science ◽

10.1287/trsc.2021.1049 ◽

2021 ◽

Author(s):

Konrad Stephan ◽

Felix Weidinger ◽

Nils Boysen

Keyword(s):

Mathematical Programming ◽

Urban Space ◽

Urban Areas ◽

Computational Study ◽

Solution Space ◽

Computational Effort ◽

Design Tool ◽

Mixed Integer ◽

Parking Lots ◽

Park Design

There is a vivid debate in cities all over the world on how to distribute the restricted space in urban areas among stakeholders. Urban design movements such as new pedestrianism or Copenhagenization advocate that too much space is attributed to cars. In this context, our research investigates the optimization of parking lots with the help of mathematical programming. For the given ground plot of a parking lot, we maximize the number of parking spaces each reachable via a driving lane, so that the urban space attributed to the parking of cars is efficiently used. Based on a grid of squares in which we rasterize the ground plot, this paper presents mixed-integer programs based on three different resolutions for orthogonal parking. Our computational study explores the tradeoff between the additional parking spaces promised by a higher resolution and the increased computational effort because of the larger solution space (and vice versa). We compare our optimization approaches with a sample of 177 real-world parking lots and show that optimization can be a serviceable car park design tool with the help of a case study.

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COMPUTATIONAL STUDY ON DESIGN SPACE EXPANSION DURING TEAMWORK

Proceedings of the Design Society ◽

10.1017/pds.2021.69 ◽

2021 ◽

Vol 1 ◽

pp. 691-700

Author(s):

Marija Majda Perisic ◽

Mario Štorga ◽

John S. Gero

Keyword(s):

Cognitive Processes ◽

Design Space ◽

Computational Study ◽

Linear Trend ◽

Solution Space ◽

Cognitive Effort ◽

Design Solution ◽

Agent Based ◽

Emerging Patterns ◽

Space Expansion

AbstractWhen observing a design space expansion during teamwork, several studies found that cumulative solution-related issues' occurrence follows a linear trend. Such findings contradict the hypothesis of solution-related issues being characteristic for the later design stages. This work relies on agent-based simulations to explore the emerging patterns in design solution space expansion during teamwork. The results demonstrate trends that accord with the empirical findings, suggesting that a cognitive effort in solution space expansion remains constant throughout a design session. The collected data on agents' cognitive processes and solution space properties enabled additional insights, which led to the detection of four distinct regimes of design solution space expansion.

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