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The purpose of this paper is to solve the problem of committing electric power generators (unit commitment, UC), considering network constraints.

The UC is first solved with a local search based meta‐heuristic, following the assumption that all generators and loads are connected to a single network node. For evaluation purposes, the economical production levels of the units committed are computed by running a pre‐dispatch algorithm where network constraints are not included. If a good quality solution is reached, an economic dispatch (ED) with network constraints is performed, where the geographic location of generators and loads are considered. Therefore, the production level of each committed generator is performed that leads to the global lowest solution cost, regarding both the generators' costs and constraints and the power system network constraints.

The algorithm proposed is computationally efficient, given the time available for decision making. In addition, the solution for this algorithm, in terms of minimization of total costs, is generally better than the solution of the two phases approach. Some contractual and legal aspects related with the injection in network connections can also be included in the model.

UC with network constraints has a large potential of use, especially for small and medium size power systems. It reflects reality in a closer way and provides a more complete and realistic knowledge about the system in operation.

The paper presents an approach where the ED with network constraints is integrated with the UC procedure. The model described is currently implemented in an EMS package offered in the market – making it a case of successful transfer from science to industry.

This paper aims to focus on the accurate analysis of the fractional heat transfer in a two-dimensional (2D) rectangular monolayer tissue with three different kinds of lateral boundary conditions and the quantitative evaluation of the degree of thermal damage and burn depth.

A symplectic method is used to analytically solve the fractional heat transfer dual equation in the frequency domain (s-domain). Explicit expressions of the dual vector can be constructed by superposing the symplectic eigensolutions. The solution procedure is rigorously rational without any trial functions. And the accurate predictions of temperature and heat flux in the time domain (t-domain) are derived through numerical inverse Laplace transform.

Comparison study shows that the maximum relative error is less than 0.16%, which verifies the accuracy and effectiveness of the proposed method. The results indicate that the model and heat source parameters have a significant effect on temperature and thermal damage. The pulse duration (Δt) of the laser heat source can effectively control the time to reach the peak temperature and the peak slope of the thermal damage curve. The burn depth is closely correlated with exposure temperature and duration. And there exists the delayed effect of fractional order on burn depth.

A symplectic approach is presented for the thermal analysis of 2D fractional heat transfer. A unified time-fractional heat transfer model is proposed to describe the anomalous thermal behavior of biological tissue. New findings might provide guidance for temperature prediction and thermal damage assessment of biological tissues during hyperthermia.

This paper aims to report theoretical and numerical results for the problem of laminar axisymmetric flow of hybrid nanofluid over a permeable non-linearly stretching/shrinking sheet with radiation effect.

The numerical solutions of the arising boundary value problem are obtained using the function bvp4c from MATLAB for different values of the governing parameters.

It is found that the solutions of the ordinary (similarity) differential equations have two branches, upper and lower branch solutions, in a certain range of the stretching/shrinking and suction parameters. To establish which of these solutions are stable and which are not, a stability analysis has been performed.

To the best of the authors’ knowledge, present results are original and new for the study of fluid flow and heat transfer over a stretching/shrinking surface, as they successfully extend the problem considered by Mustafa et al. (2015) to the case of hybrid nanofluids.

The purpose of this paper is to provide an effective members-adding method for truss topology optimization in plastic design.

With the help of the distribution of principal stress trajectories, obtained by finite element analysis of the design domain, ineffective zones for force transmission paths can be found, namely, areas whose nodes may have ersatz nodal displacements. Members connected by these nodes are eliminated and the reduced ground structure is used for optimization. Adding members in short to long order and limiting the number of members properly with the most strained ones added, large-scale truss problems in one load case and multiple-load cases are optimized.

Inefficient members (i.e. bars that fulfil the adding criterion but make no contribution to the optimal structure) added to the ground structure in each iterative step are reduced. Fewer members are used for optimization than before; therefore, faster solution convergence and less computation time are achieved with the optimized result unchanged.

The proposed members-adding method in the paper can alleviate the phenomenon of ersatz nodal displacements, enhance computational efficiency and save calculating resources effectively.

To study the steady mixed convection boundary‐layer flow of a micropolar fluid near the region of the stagnation point on a double‐infinite vertical flat plate is studied. The results of this paper are important for the researchers in the area of micropolar fluids.

For the case considered the problem reduces to a system of ordinary differential equations, which is solved numerically using the Keller‐box method. This method is very efficient for solving boundary‐layer problems and it can easily be applied to other general situations than that presented in this paper. Any PhD student can learn and apply it very easily.

Representative results for the velocity, microrotation and temperature profiles, as well as for the reduced skin friction coefficient and the local Nusselt number have been obtained for the case of strong concentration, Prandtl number of 0.7, some values of the material parameter K and the mixed convection parameter λ(≥0). Both assisting and opposing flow cases are considered. Results for the reduced skin friction coefficient and reduced local Nusselt number as well as for the reduced velocity, temperature and microrotation profiles are given in tables and figures. The obtained results are compared with ones from the open literature and it is found that they are in excellent agreement. The important conclusion is, we have been able to show that for opposing flow solutions are possible are possible only for a limited range of values of the mixed convection parameter λ.

The results of this paper are valid only in the small region around the stagnation point on a vertical surface and they are not applicable outside this region.

The theory of micropolar fluids and also the results of the present paper can be used to explain the characteristics in certain fluids such as exotic lubricants, colloidal suspensions or polymeric fluids, liquid crystals, and animal blood.

The paper is very well prepared, presented and readable. We believe that the results are original and important from both theoretical and application point of views.

This work examines the joint pricing and ordering (JPO) decisions for a loss-averse retailer with quantity-oriented reference point (RP) effect under demand uncertainty.

The demand is assumed to be uncertain with the mean and variance as the only known information. The prospect theory is used to model the retailer's expected utility. An expected utility maximization model in the distribution-free approach (DFA) is then developed. Using duality theory, the expected utility under the worst-case distribution is transformed into tractable piece-wise functions. To examine the effectiveness of the DFA in coping with the demand uncertainty, a stochastic programming model is developed and its solutions are used as benchmarks.

The proposed model and solution approach can effectively hedge against the demand uncertainty. The JPO decisions are significantly influenced by the LA coefficient and the reference level. The LA has a stronger influence than the reference level does on the expected utility. An excessive LA is detrimental while an appropriate reference level is beneficial to the retailer.

The results of this work are applicable to loss-averse retailers with the quantity-oriented RP when making JPO decisions with difficulty in predicting the demands.

The demand is assumed to be uncertain in this work, but a certain demand distribution is usually assumed in the existing literature. The DFA is used to study JPO decisions for the loss-averse retailer with quantity-oriented RP effect under the uncertain demand.

The lack of adequate information for logistics decisions and evaluating is a major problem for management. This article describes how linear programming is used to provide methodology to evaluate decisions and system performance without the availability of cost and other data. A simple application to logistics systems is discussed and its application to an actual problem is described.

This paper aims to assess the economic effects of climate change on the Mediterranean’s irrigated agriculture and how the adoption of alternative crop varieties adapted to the expected length of the growing season can be an effective adaptation measure.

A case study of two irrigation areas in Southern Portugal is used to assess the response to climate change impacts on crop yields and irrigation requirements, and an agricultural supply model is calibrated using a positive mathematical programming (PMP) approach was developed.

Climate change reduces crop yields and causes a slight decrease in irrigation requirements, which could allow an increase in the irrigated area. However, positive impacts on rural areas regarding employment and investment are not expected. The adoption of adaptation measures based on alternative crop varieties, which could maintain crop yields at current levels, increases dramatically the economic value of water and mitigates losses in farm income.

The impacts on output and input market prices, as well as other biophysical impacts (for instance, CO₂ and water availability), are important in understanding the effects of climate change on irrigated agriculture, but they were not considered in this study. While this may be a limitation, it can also be a stimulus for further research.

This is an empirical paper, whose results contribute to improving knowledge about the effects of climate change on irrigated agriculture in Mediterranean areas, namely, its economic impacts on returns and the use of agricultural resources (land, water, labour and capital). Other practical implications of the paper are associated with the methodological approach, which provides a framework able to deal with the complexity and multidimensional effects of climate change.

The results of the paper provide important information for scientists, politicians and other stakeholders about the design of more effective adaptation measures able to mitigate the effects of climate change.

Crop yields and irrigation requirements were previously calculated based on data generated by the regional climate models. This is the first time that an application is developed for Portugal. Two distinct profiles of irrigation areas were studied and a large set of crops was considered, which is not common in the existing studies. To specify the PMP approach used to calibrate the agricultural supply model, exogenous crop-specific supply elasticities were estimated through a least square model, which is not common in previous studies.

The purpose of this paper is to address a solution to the problem of defect recognition from images using the support vector machines (SVM).

A SVM‐based multi‐class pattern recognition system has been developed for inspecting commonly occurring fabric defects such as neps, broken ends, broken picks and oil stain. A one‐leave‐out cross validation technique is applied to assess the accuracy of the SVM classifier in classifying fabric defects.

The investigation indicates that the fabric defects can be classified with a reasonably high degree of accuracy by the proposed method.

The paper outlines the theory and application of SVM classifier with reference to pattern classification problem in textiles. The SVM classifier outperforms the other techniques of machine learning systems such as artificial neural network in terms of efficiency of calculation. Therefore, SVM classifier has great potential for automatic inspection of fabric defects in industry.

Introduction Properly performed management accounting variance analyses frequently generate insight by management that helps to identify factors contributing to a poorer (or better) than expected performance, and to pinpoint persons or circumstances responsible for a variance. On the other hand, incorrect or inadequate evaluations are often dysfunctional to management. The wrong problem areas may be exposed by an incorrect evaluation, valuable time and expensive effort may be wasted in analysing the wrong problems, and improper actions might be enacted that would tend to hasten an already deteriorating situation.