Adapted particle swarm optimization algorithm–based layout design optimization of passenger car cockpit for enhancing ergonomic reliability

Abstract

The mechanical reliability problem of passenger car cockpit facilities layout is increasingly complex and has potential and uncertain risks for human safety while the number of private cars is increasing. A new system of layout design optimization is proposed to solve this problem. First, the optimization sequences of facilities are determined using a hybrid method of multiple-attribute decision-making and entropy. Second, the degree of feeling crowded in the cockpit layout can be adjusted based on customers' preference. Third, an adapted particle swarm optimization algorithm is proposed to solve the problem of three-dimensional layout optimization in car cockpit human-machine interface according to the ergonomic principles, and the adapted algorithm called smoothing iteration particle swarm optimization is contrasted with those of other common algorithms to demonstrate its advantages. Finally, the optimized layout is analyzed by virtual simulations and compared with the original layout to show the feasibility and effectiveness of the proposed design system. Analysis results indicate that the optimized layout by the new particle swarm optimization can make the operation easier and safer than the original one to enhance ergonomic reliability.

An Improved Particle Swarm Optimisation Method for Performance Evaluation of Instructors

“…e performance appraisal system for instructors has always been a more complicated system project embodied in the construction of college appraisal [23][24][25]. Regarding the various indicators and factors in the assessment system, such as how to formulate specific indicators for the instructor's assessment, how to make the indicators more scientific and objective, and how to stimulate the enthusiasm of the instructor to better participate in the assessment influence in the system [26,27].…”

“…Index parameter evaluation is from 2.5 to 3.0. e range indicates an excellent value. In result this improved particle swarm can be compared with the state of the art (Liu et al, 2019). In conclusive remarks, this study is to provide state-of-the-art study for the current research on the topic of instructor performance appraisal in colleges and universities.…”

Optimization Model to Manage Ship Fuel Consumption and Navigation Time

“…Attempts are also made to use multi-objective optimization methods to design the ship room arrangement. For example, a method combining systematic layout planning and a genetic algorithm to optimize the cabin placement within ships is presented in [13], [14], [15], whereas application of the particle swarm algorithm to optimize the ship's vertical passage layout problem is presented in [16].…”

“…The analysis carried out here of the issues related to the application of multi-objective optimization methods to the various problems that arise in the operation and design of ships shows that: − this concerns a wide range of maritime industry areas, for instance: optimizing the ship's routes and schedules [1]- [6], design of the ship's arrangement [7], [12]- [17], hull and propeller shape [8]- [12], optimizing the ship's hull and propeller cooperation [18]- [22], and optimizing the maintenance process [23], [24], − these methods are based on analytical models, for example [1], [17], [25] or numerical models, for example [12], [19], [22], and in the majority, they are parametric studies, where data were obtained from the ship's historical logs or specifications of the existing ships, − these methods used various optimization algorithms, for example: exact algorithms in [1], [17], [25], approximation algorithms in [9], and metaheuristic algorithms (evolutionary algorithm [18]; genetic algorithm [13], [14] [15]; particle swarm optimization [16], [20]). Unfortunately, from the perspective of the problem discussed in this paper, i.e., supporting the selection of the commanded outputs of the ship's propulsion system, the literature review performed found no methods based on data collected during the planned sea trials regarding ship fuel consumption and speed prediction.…”

Research on building truss design based on particle swarm intelligence optimization algorithm

“…Different kinds of constraints, variables, objective functions and so on, are required for deriving different optimization criteria, so the generality is poor. The MP method can attain the global optimal solution of convex optimization and non-convex optimization problems [24]. It is a precise solution method and can be directly applied to continuous variable structure optimization.…”