To improve customer satisfaction of cold chain logistics fresh agricultural goods enterprises and reduce the comprehensive distribution cost composed fixed cost, transportation cargo damage refrigeration time penalty a multi-objective path optimization model products considering client is constructed. The solved using an enhanced Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II), differ...

This paper presents an innovative active power filter design method to simultaneously compensate the current harmonics and reactive power of a nonlinear load. The power filter integrates a passive power filter which is a RL low-pass filter placed in series with the load, and an active power filter which comprises an RL in series with an IGBT based voltage source converter. The filter is assumed...

one main group of a transportation network is a discrete hub covering problem that seeks to minimize the total transportation cost. this paper presents a multi-product and multi-mode hub covering model, in which the transportation time depends on travelling mode between each pair of hubs. indeed, the nature of products is considered different and hub capacity constraint is also applied. due to ...

In this study, our aim is to predict the compositions of zinc electroplating bath using machine learning method and optimize organic additives with NSGA-II (Non-dominated Sorting Genetic Algorithm) optimization algorithm. Mask RCNN was utilized classify coated plates according their appearance. The names classes were defined as ”Full Bright”, Fail”, ”HCD Fail” ”LCD Fail”. intersection over unio...

The aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategi...

Abstract This paper proposes a method for improving the diversity of Pareto front and uniformity non-dominated solution distributions in fast elitist sorting genetic algorithm (NSGA-II), which is an evolutionary multi-objective optimization algorithm. Conventional NSGA-II has excellent convergence to front, but it been reported that some test cases, does not produce more diverse distribution th...

This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing frame...

A new evolutionary multi-objective crowding algorithm (EMOCA) is evaluated using nine benchmark multiobjective optimization problems, and shown to produce non-dominated solutions with significant diversity, outperforming state-of-the-art multi-objective evolutionary algorithms viz., Non-dominated Sorting Genetic Algorithm – II (NSGA-II), Strength Pareto Evolutionary algorithm II (SPEA-II) and P...

This paper introduces a design for multi-objective PID controller using non-dominated sorting genetic algorithm (NSGA-II). When selecting the objectives to be optimized, it is taken into account to cover some important characteristics of the system like performance, robustness and control signals’ smoothness. The decision making is done using Level diagram tool. Three tanks liquid level system ...