Jorge Moreira da Costa

Performance Assessment of Construction Companies Integrating Key Performance Indicators and Data Envelopment Analysis

The web benchmarking systems broadly used in the construction industry (CI) are designed to provide results based on key performance indicators (KPIs). No insights concerning organization overall performance and improvements targets are available. This research aims to fulfill this gap using data envelopment analysis (DEA) as a method to complement the information provided by a set of KPIs. The methodology proposed is useful to all organizations involved in benchmarking routines. To enable a more realistic assessment of CI companies, two types of DEA models were used, one allows factor weights to vary freely and the other includes weight restrictions. These models assign an efficiency score to each organization, identifying efficient organizations and providing performance improvements targets for the others. To enable suggesting targets for all organizations, expert opinion was used to specify virtual units which were included in the efficiency assessment to define a practical frontier located beyond the productivity levels of the original DEA frontier. Based on a sample of 20 Portuguese leading contractors, the Portuguese web benchmarking system for CI, icBench, was used to demonstrate the advantages of integrating the DEA method with KPIs benchmark scores.

One Table Fits All

Tabling is an implementation technique that overcomes some limitations of traditional Prolog systems in dealing with redundant sub-computations and recursion. The performance of tabled evaluation largely depends on the implementation of the table space. Arguably, the most successful data structure for tabling is tries. However, while tries are efficient for variant based tabled evaluation, they are limited in their ability to recognize and represent repeated answers for different calls. In this paper, we propose a new design for the table space where tabled subgoal calls and/or answers are stored only once in a common global trie instead of being spread over several different tries. Our preliminary experiments using the YapTab tabling system show very promising reductions on memory usage.

Global Storing Mechanisms for Tabled Evaluation

Arguably, the most successful data structure for tabling is tries. However, while tries are very efficient for variant based tabled evaluation, they are limited in their ability to recognize and represent repeated terms in different tabled calls or/and answers. In this paper, we propose a new design for the table space where tabled terms are stored in a common global trie instead of being spread over several different tries.

A Term-Based Global Trie for Tabled Logic Programs

A critical component in the implementation of an efficient tabling system is the design of the data structures and algorithms to access and manipulate tabled data. Arguably, the most successful data structure for tabling is tries. However, when used in applications that pose many queries and/or have a large number of answers, tabling can build arbitrarily many and/or very large tables, quickly filling up memory. In this paper, we propose a new design for the table space organization where all terms in tabled subgoal calls and tabled answers are represented only once in a common global trie instead of being spread over several different trie data structures. Our initial experiments using the YapTab tabling system show significant reductions on memory usage without compromising running time.

The Use of Generic Cost/Performance Ratios in the Financing of Housing

ABSTRACT Design Quality Evaluation Methods have been used in several countries as a means to improve housing quality. A simplified approach suitable to use as support to financing procedures is proposed.