Optimizing the operation of reservoir involving ecological and environmental (eco-environmental) objectives is challenging due to the often competing social-economic objectives. Non-dominated Sorting Genetic Algorithm-II is a popular method for solving multi-objective optimization problems. However, within a complex search space, the NSGA-II population (i.e., a group of candidate solutions) may...

The Evolutionary Computation has grown much in last few years. Inspired by biological evolution, this field is used to solve NP-hard optimization problems to come up with best solution. TSP is most popular and complex problem used to evaluate different algorithms. In this paper, we have conducted a comparative analysis between NSGA-II, NSGA-III, SPEA-2, MOEA/D and VEGA to find out which algorit...

using new approaches to optimize the process of power transmission line routing can solve many complex problems which power transmission line routing decision-makers are faced. due to the expansion of involved parameters we can consider multi-objective evolutionary algorithms as appropriate method in this area. in this thesis with using multi-objective evolutionary algorithms nsga-ii and offere...

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...

This paper proposes a novel Multi-Objective Evolutionary Algorithm for hardware software partitioning of embedded systems. Customized genetic algorithms (GA) have been effectively used for solving complex optimization problems (NP Hard) but are mainly applied to optimize a particular solution with respect to a single objective. Many real world problems in embedded systems have multiple objectiv...

With the development of customization concept, small-batch and multi-variety production will become one major modes, especially for fast-moving consumer goods. However, this mode has two issues: high cost long manufacturing period. To address these issues, study proposes a multi-objective optimization model flexible flow-shop to optimize scheduling, which would maximize efficiency by minimizing...

Trajectory planning is always a hot issue for harvesting manipulator in practice considering that the limitations of mechanical structure and other nonlinear factors lead to long harvest time, big jerk high energy consumption. The cubic spline algorithm, fifth-order polynomial interpolation fusing algorithm are used shorten reduce enhance robustness manipulator, respectively. Then trajectory pr...

This study proposes a bi-objective model for capacitated multi-vehicle allocation of customers to potential distribution centers (DCs).The optimization objectives are to minimize transit time and total cost including opening cost, assumed for opening potential DCs and shipping cost from DCs to the customers where considering heterogeneous vehicles lead to a more realistic model and cause more c...

This paper considers a multi-period, multi-product inventory-routing problem in a two-level supply chain consisting of a distributor and a set of customers. This problem is modeled with the aim of minimizing bi-objectives, namely the total system cost (including startup, distribution and maintenance costs) and risk-based transportation. Products are delivered to customers by some heterogeneous ...

Today’s logistic systems in companies depend on optimum solutions of Facility Location-Allocation (FLA) problems in order to minimize cost values the company is dealing with. Therefore, FLA plays an important role in nowadays business environment. In this paper, a Hybrid Genetic Algorithm (HGA) is proposed to solve FLA. The HGA is a combination of Genetic Algorithm and Tabu Search while NSGA II...