Competitive Boolean Function Evaluation: Beyond Monotonicity, and the Symmetric Case

We study the extremal competitive ratio of Boolean function evaluation. We provide the first non-trivial lower and upper bounds for classes of Boolean functions which are not included in the class of monotone Boolean functions. For the particular case of symmetric functions our bounds are matching and we exactly characterize the best possible competitiveness achievable by a deterministic algorithm. Our upper bound is obtained by a simple polynomial time algorithm.Comment: 15 pages, 1 figure, to appear in Discrete Applied Mathematic

Determinants of tourism destination competitiveness in the countries most visited by international tourists: Proposal of a synthetic index

Tourism destination competitiveness is a multidimensional concept that is widely studied in the academic literature, but multiple factors make its measurement a difficult task. In this article, we design a synthetic index to rank the 80 countries that attract the majority of international tourists by level of tourism competitiveness. In order to do this, we use all of the simple variables included in the 2017 Travel & Tourism Competitiveness Index, proposing a new methodology for the construction of this synthetic index, which it solves the problems of aggregation of variables expressed in different measures, arbitrary weighting and duplicity of information; issues that remain unresolved by the TTCI. Likewise, we analyse the most influential dimensions in tourism competitiveness. Air transport infrastructures, cultural resources and ICT readiness are the key dimensions that explain the main disparities.Funding Agency Spanish Ministry of Economy, Industry and Competitiveness State Research Agency (SRA) European Union (EU) ECO2017-86822-Rinfo:eu-repo/semantics/publishedVersio

Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO

The design of spacecraft trajectories for missions visiting multiple celestial bodies is here framed as a multi-objective bilevel optimization problem. A comparative study is performed to assess the performance of different Beam Search algorithms at tackling the combinatorial problem of finding the ideal sequence of bodies. Special focus is placed on the development of a new hybridization between Beam Search and the Population-based Ant Colony Optimization algorithm. An experimental evaluation shows all algorithms achieving exceptional performance on a hard benchmark problem. It is found that a properly tuned deterministic Beam Search always outperforms the remaining variants. Beam P-ACO, however, demonstrates lower parameter sensitivity, while offering superior worst-case performance. Being an anytime algorithm, it is then found to be the preferable choice for certain practical applications.Comment: Code available at https://github.com/lfsimoes/beam_paco__gtoc

Parallel machine scheduling with precedence constraints and setup times

This paper presents different methods for solving parallel machine scheduling problems with precedence constraints and setup times between the jobs. Limited discrepancy search methods mixed with local search principles, dominance conditions and specific lower bounds are proposed. The proposed methods are evaluated on a set of randomly generated instances and compared with previous results from the literature and those obtained with an efficient commercial solver. We conclude that our propositions are quite competitive and our results even outperform other approaches in most cases

Study on Performance Appraisal Method of Vocational Education Teachers using PROMETHEE II

Evaluating vocational education teachers’ performance is an important link of teaching management and an important guarantee of improving teaching quality. In conducting teaching, research and community service, vocational education teachers should weight more on quality than quantity. In this context, individual habit reacts to the demanded jobs which are influenced by his/her knowledge, attitude, and skill. Teacher’s performance evaluation is nothing but a Multi Criteria Decision Making Problem (MCDM). There are several quality attributes that influence the efficiency of a potential vocational education teacher while guiding his/her students towards a positive and value added academic outcome. However, the importance of quality attributes may differ from individuals’ perspective. In other words, different attributes may have different weightage according to their priority of significance while evaluating quality/performance level of a vocational education teacher. This paper makes the vocational education teachers’ performance appraisal quantitative and determines the evaluation index based on academic performance. Criteria for performance are: teaching load, publication, research, conferencing, consultancy, services, teaching attitude, teaching content, teaching method, and teaching effect. The Analytic Hierarchy Process (AHP) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) II analysis were used in performance appraisal. Application feasibility of this method approach and guidelines in solving such a multi-attribute decision making problem has been described illustratively in this paper. It is also observed that this MCDM approach is a viable tool in solving the teacher selection decision problems. It allows the decision maker to rank the candidate alternatives more efficiently and easily. Keywords: performance, teaching, Analytic Hierarchy Process, PROMETHEE II