Infeasibility handling in genetic algorithm using nested domains for production planning

In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Formalization of an architectural model for exception handling coordination based on CA action concepts

Architectures based on Coordinated Atomic action (CA action) concepts have been used to build concurrent fault-tolerant systems. This conceptual model combines concurrent exception handling with action nesting to provide a general mechanism for both enclosing interactions among system components and coordinating forward error recovery measures. This article presents an architectural model to guide the formal specification of concurrent fault-tolerant systems. This architecture provides built-in Communicating Sequential Processes (CSPs) and predefined channels to coordinate exception handling of the user-defined components. Hence some safety properties concerning action scoping and concurrent exception handling can be proved by using the FDR (Failure Divergence Refinement) verification tool. As a result, a formal and general architecture supporting software fault tolerance is ready to be used and proved as users define components with normal and exceptional behaviors. (C) 2010 Elsevier B.V. All rights reserved.

Decolourisation of real textile waste using electrochemical techniques: Effect of electrode composition

The present paper presents the study of the decolourisation of real textile effluent by constant current electrolysis in a flow-cell using a DSAO type material. The effect of using different anode materials (Ti/Ru0.3Ti0.7O2; Ti/Ir0.3Ti0.7O2; Ti/RuxSn1-xO2, where X = 0.1, 0.2 or 0.3) on the efficiency of colour removal is discussed. Attempts to perform galvanostatic oxidation (40 and 60 mA cm(-2)) on the as-received effluent demonstrate that colour removal and total organic carbon (TOC) removal are limited. In this case the greatest degree of colour removal is achieved when anode containing 90% SnO2 is used. If the conductivity of the effluent is increased by adding NaCl (0.1 mol L-1) appreciable colour/TOC removal is observed. The efficiencies of colour and TOC removal are discussed in terms of the energy per order (E-EO/kWhm(-3) order(-1)) and energy consumption (E-C/kW h kg(-1) TOC), respectively. Finally, the extent of colour removal is compared to consent levels presented in the literature. (C) 2008 Elsevier B.V. All rights reserved.

Structure and Applications of a Rhamnolipid Surfactant Produced in Soybean Oil Waste

Soybean oil soapstock was utilized as an alternative carbon source for the production of rhamnolipids by Pseudomonas aeruginosa LBI strain. The chemical composition and properties of the rhamnolipid mixture obtained were determined to define its potential applications. The chemical characterization of the rhamnolipid has revealed the presence of ten different homologues. The monorhamnolipid RhaC(10)C(10) and the dirhamnolipid Rha(2)C(10)C(10) were the main components of the mixture that showed predominance of 44% and 29%, respectively, after 144-h of cultivation. The biosurfactant was able to form stable emulsions with several hydrocarbons and showed excellent emulsification for soybean oil and chicken fat (100%). The rhamnolipid removed 67% of crude oil present in sand samples and presented antimicrobial activity against Bacillus cereus and Mucor miehei at 64 mu g/mL and inhibition of Neurospora crassa, Staphylococcus aureus, and Micrococcus luteus at 256 mu g/mL. The results demonstrated that the rhamnolipid produced in soybean oil soapstock can be useful in environmental and food industry applications.