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For several years great effort has been devoted to the study of Architectural Design Optimization (ADO). However, although in the recent years ADO has attracted much attention from academia, optimization methods and tools have had a limited influence on the architectural profession. The aim of the study is to reveal users' expectations from the optimization tools and define limitations preventing wide-spread adaptation of the optimization solvers in the architectural practice. The paper presents the results of the survey "Optimization in the architectural practice" conducted between December 2015 and February 2016 on 165 architectural trainees and practising architects from 34 countries. The results show that there is a need for an interactive multi-objective optimization tool, as 78% respondents declared that a multi-objective optimization is more necessary in their practice than a single objective one and 91% of them acknowledged the need for choice of promising solutions during optimization process. Finally, it has been found that daylight, structure and geometry are three top factors which architects are interested in optimizing.

We study the labeled multi-robot path planning problem in continuous 2D and 3D domains in the absence of obstacles where robots must not collide with each other.For an arbitrary number of robots in arbitrary initial and goal arrangements, we derive a polynomial time, complete algorithm that produces solutions with constant-factor optimality guarantees on both makespan and distance optimality, in expectation, under the assumption that the robot labels are uniformly randomly distributed.Our algorithm only requires a small constant factor expansion of the initial and goal configuration footprints for solving the problem, i.e., the problem can be solved in a fairly small bounded region.Beside theoretical guarantees, we present a thorough computational evaluation of the proposed solution. In addition to the baseline implementation, adapting an effective (but nonpolynomial time) routing subroutine, we also provide a highly efficient implementation that quickly computes near-optimal solutions. Hardware experiments on the microMVP platform composed of non-holonomic robots confirms the practical applicability of our algorithmic pipeline.

The study reports treatment and follow-up of compulsive drug-consuming patients (mainly of coca paste). The program used was based on a behavioral cognitive and instructional model. The traditional functional analysis was modified to include the therapeutical work in seven behavioral areas: (1) drug use; (2) behavior during free time; (3) behavior at work; (4) social behavior; (5) self- and environmental management behaviors; (6) problem solving and decision-making behaviors; (7) recognition, evaluation, and modification of irrational beliefs. For each area objectives, therapeutical procedures, control and evaluation methods, and termination criteria were determined. Patients engaged in a multiple activity program and received individual and group therapy. Out of 223 male patients, 130 were discharged (that is, they fulfilled all the conditions stated by the program) and 93 patients abandoned treatment. For evaluation purposes a test was used to determine the accomplishment of the behavioral objectives. Follow-up interviews after 6 to 72 months showed that although 24 patients relapsed to drug use, 106 (81.48%) of the patients who had finished the program restrained from using drugs and obtained high scores in all seven behavioral areas.