Handling construction pollutions using multi‐objective optimization

Quantitative assessment of emissions associated with construction projects should be carried out during the planning phase of the projects. This is important to detect and highlight any excesses of residuals during the construction phase. A newly developed framework is proposed to handle construction pollution using multi‐objective optimization. The approach, utilized by the proposed framework, is based on calculating the generated pollution for each activity involved in the project, as a result of dust, harmful gases and noise. The results of the quantitative assessment are integrated in a utility function that expresses the amount of total pollution. Then, evolutionary genetic algorithms (GAs) are used to carry multi‐objective optimization, considering three objective functions (project duration, project cost and total pollution). The proposed application considers the dynamic nature of construction activities including different types of relationships and the change of activities' criticality. An actual case study is worked out to demonstrate the practical use of the proposed framework and to investigate the sensitivity of its parameters.     

Kinetic model of sugar diffusion from sugar beet tissue treated by pulsed electric field

Extraction of sugar from sugar beet slices was studied following various pulsed electric field (PEF) treatments (intensities from 300 to 800 V cm^?1 and number of pulses varying between 50 and 1000). Slices treated by PEF were immersed in water at ambient temperature at a liquid/solid ratio of 3. A significant increase in extraction yield was observed. This enhancement was due to permeabilisation of the cellular membrane and to the additional quantity of juice appearing on the surface of slices after PEF treatment being extracted rapidly by convection. The optimal conditions of PEF treatment were an intensity of 670 V cm^?1 and 250 pulses. The extraction kinetics was studied on the basis of two approaches: Fick's diffusion equation and a two‐exponential kinetic model. The coefficient of diffusion was only slightly influenced by the conditions of PEF treatment. The two‐exponential model successfully described both the rapid and prolonged stages of extraction. By heating the solution at mild temperatures of 30–50 °C, the coefficient of diffusion was increased and the kinetics of extraction was enhanced. The quality of cellular juice obtained after PEF treatment was higher than that of juice obtained after thermal pretreatment at 75 °C. Copyright © 2004 Society of Chemical Industry     

Comparative study of dewatering characteristics of metal precipitates generated during treatment synthetic polymetallic and AMD solutions

The sludge dewatering characteristics expressed in terms of settling, filtration and centrifugation of metal precipitates generated during treatment of polymetallic solutions and synthetic acid mine drainage have been evaluated in this research. Results show that dewatering properties of metallic sludge vary depending on the type of matrix (Cl⁻; SO₄²⁻), precipitating agent, and metals present in effluent. Metal hydroxides (at pH 10.0) and metal phosphates precipitates (at pH 7.0) are amorphous in nature, thus difficult to dewater. In these treatment methods, the substitution of chloride matrix by sulphate one improves considerably dewatering properties (specific resistance to filtration = 6.60 × 10¹³ and 2.35 × 10¹³ m/kg for the chloride and sulphate matrix, respectively). In the case of sulphide and carbonate treatments (pH 8.0), precipitates obtained are semi crystalline, and crystalline form, respectively, and no influence of the matrix was detected on dewatering characteristics.     

Evaluation of harvested mushrooms and viability of Agaricus bisporus growth using casing materials made from spent mushroom substrate

The present work evaluates of harvested mushroom and viability of Agaricus bisporus growth in several casing materials based on spent mushroom substrate. The experiment consisted of eight casing layer, which six were made with spent mushroom substrate. The results confirm the usefulness of reincorporating the spent substrate in new cultivation cycles as an ingredient of casing mixtures. In general, biological efficiency was high, three of the SMS based‐casings surpassing the threshold value of 100 kg 100 kg^?1 of compost. The high electrical conductivity of mixtures containing a large proportion of spent substrate limits the extent to which it can be used, although mixing it with other materials (such as peat) reduces these values to acceptable levels. In short, it makes economic and environmental sense to reuse spent mushroom substrate as an ingredient of alternative casing materials.     

WCOID-DG: An approach for case base maintenance based on Weighting, Clustering, Outliers, Internal Detection and Dbsan-Gmeans

The success of the Case Based Reasoning system depends on the quality of the case data and the speed of the retrieval process that can be costly in time, especially when the number of cases gets bulky. To guarantee the system?s quality, maintaining the contents of a case base (CB) becomes unavoidably. In this paper, we propose a novel case base maintenance policy named WCOID-DG: Weighting, Clustering, Outliers and Internal cases Detection based on Dbscan and Gaussian means. Our WCOID-DG policy uses in addition to feature weights and outliers detection methods, a new efficient clustering technique, named DBSCAN-GM (DG) which is a combination of DBSCAN and Gaussian-Means algorithms. The purpose of our WCOID-GM is to reduce both the storage requirements and search time and to focus on balancing case retrieval efficiency and competence for a CB. WCOID-GM is mainly based on the idea that a large CB with weighted features is transformed to a small CB with improving its quality. We support our approach with empirical evaluation using different benchmark data sets to show its competence in terms of shrinking the size of the CB and the research time, as well as, getting satisfying classification accuracy.     

Modelling and analysis for sequentially optimising production,maintenance and delivery activities taking into account product returns

This paper develops and analyses a stochastic optimisation problem with a service level constraint for generating a sequentially optimal plan of production, maintenance and delivery activities in a deteriorating manufacturing system. Stochastic demand along with product returns are both assumed the latter of which allows for restocking products returned by the customer which are still new and thus in saleable condition. A constrained production/maintenance/delivery problem with service level, stochastic demand, delivery time, failure rate and product returned is formulated based on quadratic model. This quadratic formulation is adapted to provide an inventory, delivery, production and maintenance policies. The objective of this paper is to study the delivery time influence on the planning of the production, maintenance and delivery activities. Finally, we present simulation results to illustrate the exploitation of the proposed approach.     

Forecasting and maintenance problem under subcontracting constraint with transportation delay

In this paper, a forecasting production/maintenance optimization problem has been proposed with a random demand and single machine M₁ on a finite horizon. The function rate of the machine M₁ is depending on the production rate for each period of the forecasting horizon. In order to satisfy the customer, a subcontracting assures the rest of the production through machine M₂ with transportation delay. An analytic formulation of the problem has been proposed using a sequential computation of the optimal production plan for which an optimal preventive maintenance policy has been calculated based on minimal repair. Firstly, we find, the optimal production plans of principal and subcontracting machines, which minimises the total production and inventory cost for the cases without and with returned products under service level and subcontracting transportation delay. Secondly, we determine a joint effective maintenance policy with the optimal production plan, which integrates the various constraints for the production rates, the transportation delay and the returned production deadline. Numerical results are presented to highlight the application of the developed approach and sensitivity analysis shows the robustness of the model.