Abstract
This paper is divided into three parts: the first one introduces SADEX, a fuzzy Case Based Reasoning (CBR) Expert System (ES) for fault diagnosis. The second focus on its observation relevance factors and shows how the results are in entire agreement with the relevance concept introduced by Robertson and Spark-Jones in their well known and proved technique of document retrieval. Finally we describe how the equipment composition information can be used to generalize and adapt case solutions to unknown occurrences. This generalization is based on a taxonomic similarity between functionally autonomous modules (FAM) or components. Some formulae for evaluating this similarity are derived.

Abstract
In industry, spare equipments are often shared by many workplaces with identical equipments to assure the production rate required to fulfill delivery dates. These types of systems arc called "Maintenance Float Systems". The main objective of managers that deal with these types of systems is to assure the required capacity to deliver orders on time and at minimum cost. Not delivering on time has often important consequences; it call cause loss of costumer goodwill, loss of sales and call damage organization's image. Maintenance cost is the indicator more frequently used to configure maintenance float systems and to invest in maintenance workers or spare equipments. Once the system is configured, other performance indicators must be used to characterize and measure the efficiency of the system. Different improvement initiatives call be performed to enhance the performance of maintenance float systems: performing preventive maintenance actions, implementation of autonomous maintenance, improvement of equipments maintainability, increase of maintenance crews' efficiency etc. "Carrying out improvement based on facts" is a principle of Total Quality Management (TQM) in order to step to business excellence. It requires monitoring processes through performance measures. This work aims to characterize and highlight the differences and relationships between three types of performance measures-equipment availability, equipment utilization and workplace occupation, in the context of maintenance float system. Definitions and expressions of these three indicators are developed for maintenance float systems. The relationship between maintenance float systems efficiency and the referred indicators is shown. Other indicators are also proposed and compared with the first ones (number of standby equipments, queue length etc.).

Abstract
Adsorption equilibrium of fructose, glucose and sucrose was evaluated on sulfonated poly(styrene-co-divinylbenzene) cation-exchange resins. Two types of resins were used: potassium (K(+)) gel-type and sodium (Na(+)) macroporous resins. Influence of the cation and effect of the resin structure on adsorption were studied. The adsorption isotherms were determined by the static method in batch mode for mono-component and multi-component sugar mixtures, at 25 and 40 degrees C, in a range of concentrations between 5 and 250gL(-1). All adsorption isotherms were fitted by a linear model in this range of concentrations. Sugars were adsorbed in both resins by the following order: fructose > glucose > sucrose. Sucrose was more adsorbed in the Na(+) macroporous resin, glucose was identically adsorbed, and fructose was more adsorbed in the K(+) gel-type resin. Data obtained from the adsorption of multi-component mixtures as compared to the mono-component ones showed a competitive effect on the adsorption at 25 degrees C, and a synergetic effect at 40 degrees C. The temperature increase conducted to a decrease on the adsorption capacity for mono-component Sugar mixtures, and to an increase for the multi-component mixtures. Based on the selectivity results, K(+) gel-type resin seems to be the best choice for the separation of fructose, glucose and sucrose, at 25 degrees C.

Abstract
Semi-infinite programming (SIP) problems arise in several engineering areas such as, for example, robotic trajectory planning, production planning, digital filter design and air pollution control. In spite of being an active research area with many seminal works it lacks available software that could be used by the research community. The only exceptions are the fseminf MATLAB function, available in the Optimization Toolbox, and the NSIPS solver, but neither of them provide an implementation of a method belonging to the well known reduction type class. This paper proposes an implementation of a reduction type algorithm base on a penalty technique and provides a compare between several well known penalty functions. The provided numerical results with a significant number of SIP test problems are reported as performance profiles.

Abstract
Containers have been used in past decades increasingly as one of the most important transportation tools. Containers have revolutionized cargo shipping and thus changed the world trade systematically. Container terminals as the transhipment facility play a valuable role in performance of this transportation system. Improvement of this facility has been widely considered in literatures. Automated container terminals (ACTs) have been introduced to pursue this purpose. In ACTs various transport vehicles are automated and integrated to each other. Automated guided vehicles (AGVs) are used in ACTs to handle containers between quay cranes and storage yards. Usually scheduling of the AGVs is known as the key factor to improve the performance of ACTs. This paper proposed a heuristic algorithm to schedule the AGVs concurrently with quay cranes. A genetic algorithm is proposed to optimize the simultaneous scheduling of AGVs and QCs. The results showed that proposed genetic algorithm can be used in practical implications while its running time is reasonably low.

Abstract
Complex production systems can produce more than one part type. For these systems, production rate and priority of production for each part type is determined by production controllers. In this paper, genetic fuzzy logic control (GFLC) methodology is used to develop two production control architectures namely "genetic distributed fuzzy" (GDF), and "genetic supervisory fuzzy" (GSF) controllers. Previously these controllers have been applied to single-part-type production systems. in the new approach the GDF and GSF controllers are developed to control complex production systems. The methodology is illustrated and evaluated using two test cases; two-part-type production line and re-entrant production systems. Genetic algorithm is used to tune the membership functions of input variables of GSF or GDF controllers. The objective function of the GSF controller minimizes the production cost based on work-in-process (WIP) and backlog costs, while surplus minimization is considered by GDF controller. The results show that GDF and GSF controllers can improve the performance of production systems. GSF controllers decrease the WIP level and its variations. GDF controllers show their abilities in reducing the backlog level but generally, production cost for GDF controller is greater than GSF controller.