A data-driven approach for the optimization of a heating, ventilation, and air conditioning (HVAC) system in an office building is presented. A neural network (NN) algorithm is used to build a predictive model since it outperformed five other algorithms investigated in this paper. The NN-derived predictive model is then optimized with a strength multi-objective particle-swarm optimization (S-MO...

The experimental investigations of the delamination factor of glass fiber reinforced plastic at different cutting parameters are reported in this study. This paper has involved the determination of different factors affecting the hole quality and cause of delamination in a glass fiber reinforced plastic. The various process parameters like different twist drill bits of different materails, diff...

Abstract Distributed power can effectively alleviate the problems of environmental pollution and energy shortage. Based on consideration low-carbon benefits DG, a multi-objective mathematical model with minimal system carbon dioxide emissions, minimum annual network loss cost, voltage deviation distribution is established for multi-type DG access location capacity. This solved using MOPSO algor...

This paper presents a particle swarm optimisation (PSO) based multi-objective feature selection approach to evolving a set of non-dominated feature subsets and achieving high classification performance. Firstly, a pure multi-objective PSO (named MOPSO-SRD) algorithm, is applied to solve feature selection problems. The results of this algorithm is then used to compare with the proposed a multi-o...

Software cost estimation is the process of predicting the effort required to develop a software system. The basic input for the software cost estimation is coding size and set of cost drivers, the output is Effort in terms of Person-Months (PM’s). Here, the use of support vector regression (SVR) has been proposed for the estimation of software project effort. We have used the COCOMO dataset and...

This paper presents a bi-objective MIP model for the flexible flow shop scheduling  problem (FFSP) in which the total weighted tardiness and the energy consumption are minimized simultaneously. In addition to considering unrelated machines at each stage, the set-up times are supposed to be sequence- and machine-dependent, and it is assumed that jobs have different release tim...

[1] Corresponding author e-mail: [email protected]   [1] Corresponding author e-mail: [email protected]   Lot-sizing problems (LSPs) belong to the class of production planning problems in which the availability quantities of the production plan are always considered as a decision variable. This paper aims at developing a new mathematical model for the multi-level ca...

The layout of facilities in a logistics scenario involves not only the working responsible for processing materials but also transport lines transporting materials. traditional facility methods do take into account transportation nor calculate material handling cost by Manhattan distance, thus failing to fulfill actual requirements industrial scenarios. In this paper, algorithm framework MOSA-F...