In multi-objective particle swarm optimization (MOPSO), a proper selection of local guides significantly influences detection of non-dominated solutions in the objective/solution space and, hence, the convergence characteristics towards the Pareto-optimal set. This paper presents an algorithm based on simple heuristics for selection of local guides in MOPSO, named as HSG-MOPSO (Heuristics-based...

In order to achieve rapid and fair distribution of emergency supplies after a large-scale sudden disaster, this paper constructs comprehensive time perception satisfaction function material loss pain portray the perceived disaster victims based on objective constraints such as limited transport, multimodal transport supply being less than demand, at same considers subjective quantity under rati...

Particle swarm optimization (PSO) has received increasing attention in solving multi-objective economic dispatch (ED) problems in power systems because of parallel computation, faster convergence, and easier implementation. This paper presents a detailed overview of multi-objective particle swarm optimization (MOPSO) and provides a comprehensive survey on its applications in power system econom...

this paper explores the capabilities of multi-objective particle swarm optimization algorithmin a simulation-optimization model for solving waste load allocation problems. the main goals are totaltreatment costs, violation of the water quality standards and equity. in this research, the water qualitysimulation model is coupled with a multi-objective optimization model, mopso. in order to derive...

Model predictive control (MPC) is a promising approach to the lateral and longitudinal of autonomous vehicles. However, parameterization MPC with respect high-level requirements such as passenger comfort, well tracking, challenging. Numerous tuning parameters conflicting need be considered. In this paper, we formulate task multi-objective optimization problem. Its solution demanding for two rea...

Selecting team players is a crucial and challenging task demanding considerable amount of thinking hard work by the selectors. The present study formulated selection an IPL as multi-objective optimization problem with objectives maximizing batting bowling performance squad, in which player’s estimated using efficient Batting Performance Factor Combined Bowling Rate. Also, proposed model tries t...