For the particle swarm collaborative practicability algorithm, when extended from single objective to multiobjective problem, the storage and maintenance of the partial differential exact solution sets occurs. And the selection of global and personal exact solutions, balance between exploitation and exploration and other problems also occur. In this paper, the diversity and evolution state of p...

In all-electric navy ships, severe damage or faults may occur during different conditions. As a result, critical loads may suffer from power deficiencies, ultimately leading to a complete system collapse. Therefore, a fast reconfiguration of shipboard power system (SPS) is necessary to serve the critical loads. This work proposes a novel swarm intelligent algorithm based on dynamic neighborhood...

Stock traders consider several factors or objectives in making decisions. Moreover, they differ in the importance they attach to each of these objectives. This requires a tool that can provide an optimal tradeoff among different objectives, a problem aptly solved by a multi-objective optimization (MOO) system. This paper aims to investigate the application of multi-objective optimization to end...

Estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. This study aimed to use the particle swarm optimization (PSO) algorithm for automatic calibration of the HEC-HMS hydrologic model, which includes a library of different event-based models for simulating the rainfall-runoff pr...

The Combinatorial problems are real world decision making problem with discrete and disjunctive choices. When these decision making problems involve more than one conflicting objective and constraint, it turns the polynomial time problem into NP-hard. Thus, the straight forward approaches to solve multi-objective problems would not give an optimal solution. In such case evolutionary based meta-...

In this paper, we model a multi-mode time-cost-quality trade-off project scheduling problem under generalized precedence relations using mixed-integer mathematical programming. Several solution procedures, including the classic epsilon-constraint (CEC) method, the efficient epsilonconstraint (EEC) method, dynamic self-adaptive multi-objective particle swarm optimization (DSAMOPSO), and the mult...

This paper presents the optimal placement of multiple Dispersed Generators using multi-objective optimization. The optimization is carried out with objectives namely active power loss, reactive power loss, voltage deviation and overall economy. The multi-objective optimization and accounting conflicting objectives are realized through Particle Swarm Optimization with fuzzy decision approach to ...

In this paper, the ability of Immune Algorithm (IA) is investigated for VAr planning with the Static Var Compensator (SVC) in a large-scale power system. To enhance voltage stability, the planning problem is formulated as a multi-objective optimization problem for maximizing fuzzy performance indices. The multi-objective VAr planning problem is solved by the fuzzy IA and the results are compare...