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The wood industry produces large amounts of wood waste. This waste usually contains a number of nonwood materials, such as paints or varnishes. In this study, the pyrolysis characteristics of wood waste containing synthetic, polyurethane, and polyester varnishes were investigated for conversion into renewable liquid fuels. The elemental analysis and higher heating values of the biooils were determined. The chemical compounds present in the bio-oils obtained at an optimum temperature were identified by gas chromatography/mass spectroscopy analysis. The product yields and compositions were affected by the types of varnishes. The maximum bio-oil yield of 46.7% was obtained from pyrolysis of waste wood containing polyester varnish at a final pyrolysis temperature of 500 °C. The bio-oil produced from wood waste containing varnishes was composed mainly of phenols, aldehydes, acids, ketones, alcohols, benzenes, and N-containing compounds. The phenols accounted for the largest amount of compounds in the bio-oils. Therefore, the bio-oil produced from varnished wood waste could be a potential substitute for biofuels and green chemicals.

In this study, a cutting stock problem is addressed to determine the width/length of the wooden boards and select lumber in standard lengths for cutting a cable spool. A nonlinear mathematical model is introduced using Pythagoras' theorem. The aim is to minimize the total length of lumber used and equivalently the total amount of wood wasted. To reduce the computational burden, the mathematical model is decomposed into two submodels for sizing and cutting decisions, and a two-stage decomposition algorithm is proposed for solving the submodels subsequently. A simulated annealing metaheuristic combining the first-fit decreasing and increasing techniques (SA-FFD/I) is proposed to show the computational efficiency of the decomposition approach. The savings on the total length of lumber used and the total amount of wood wasted in production are achieved by the decomposition algorithm, which is 8% and 86.4% on average compared to the SA-FFD/I heuristic. Accordingly, a numerical analysis is conducted on a real case to assess how capacity load and demand pattern scenarios impact the solution. The ratio between the total amount of wood waste and the total length of lumber does not exceed 2.54% for a weekly planning horizon.

 This paper is dedicated to developing an ANN model in order to model the pyrolysis liquid product  Artificial neural networks (ANNs) have been widely used in the field of process simulation as a result of its ability to solve complex and multivariable problems.  Pyrolysis is a thermal decomposition process converting biomass into char (solid), bio-oil (liquid), and gas products

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