Presenting the Multi-Objective Optimization Model of Search and Rescue Network

The Search and Rescue Network (SAR) is a kind of emergency network that pursuit people in need or imminent danger. This paper aims using a priori optimization to demonstrate the optimal assignment of HFDF receivers to the Generalized Search and Rescue (GSAR) network, which is independent of the weighting of the transmitter areas. The mathematical model seeks two objectives, the first one is maximizing the expected number of LOBs for HFDF receivers. The second is providing a fair share number of HFDF receivers allowed to cover the frequency. The result shown the efficiency of presented model ran by CPLEX toolbox of MATLAB 2020 software.

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Multi-Objective Optimization Design of Screw Conveyor Using Genetic Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.732-733.402 ◽

2013 ◽

Vol 732-733 ◽

pp. 402-406

Author(s):

Duan Yi Wang

Keyword(s):

Genetic Algorithm ◽

Mathematical Model ◽

Optimization Design ◽

Optimization Problem ◽

Machine Design ◽

Screw Conveyor ◽

Optimized Design ◽

Multi Objective Optimization ◽

Multi Objective ◽

The Mathematical Model

The weight minimum and drive efficiency maxima1 of screw conveyor were considered as double optimizing objects in this paper. The mathematical model of the screw conveyor has been established based on the theory of the machine design, and the genetic algorithm was adopted to solving the multi-objective optimization problem. The results show that the mass of spiral shaft reduces 13.6 percent, and the drive efficiency increases 6.4 percent because of the optimal design based on genetic algorithm. The genetic algorithm application on the screw conveyor optimized design can provided the basis for designing the screw conveyor.

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Multi-objective TMA management optimization using the point merge system

Aircraft Engineering and Aerospace Technology ◽

10.1108/aeat-09-2019-0181 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Ramazan Kursat Cecen

Keyword(s):

Mathematical Model ◽

Mixed Integer ◽

Optimization Approach ◽

Multi Objective Optimization ◽

Content Type ◽

Multi Objective ◽

First Come First Serve ◽

Management Optimization ◽

The Mathematical Model ◽

Single Objective

Purpose The purpose of this study is to provide conflict-free operations in terminal manoeuvre areas (TMA) using the point merge system (PMS), airspeed reduction (ASR) and ground holding (GH) techniques. The objective is to minimize both total aircraft delay (TD) and the total number of the conflict resolution manoeuvres (CRM). Design/methodology/approach The mixed integer linear programming (MILP) is used for both single and multi-objective optimization approaches to solve aircraft sequencing and scheduling problem (ASSP). Compromise programming and ε-constraint methods were included in the methodology. The results of the single objective optimization approach results were compared with baseline results, which were obtained using the first come first serve approach, in terms of the total number of the CRM, TD, the number of aircraft using PMS manoeuvres, ASR manoeuvres, GH manoeuvres, departure time updates and on-time performance. Findings The proposed single-objective optimization approach reduced both the CRM and TD considerably. For the traffic flow rates of 15, 20 and 25 aircraft, the improvement of CRM was 53.08%, 41.12% and 32.6%, the enhancement of TD was 54.2%, 48.8% and 31.06% and the average number of Pareto-optimal solutions were 1.26, 2.22 and 3.87, respectively. The multi-objective optimization approach also exposed the relationship between the TD and the total number of CRM. Practical implications The proposed mathematical model can be implemented considering the objectives of air traffic controllers (ATCOs) and airlines operators. Also, the mathematical model is able to create conflict-free TMA operations and, therefore, it brings an opportunity for ATCOs to reduce frequency occupancy time. Originality/value The mathematical model presents the total number of CRM as an objective function in the ASSP using the MILP approach. The mathematical model integrates ATCOs’ and airline operators’ perspective together with new objective functions.

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Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

Sustainability ◽

10.3390/su13041929 ◽

2021 ◽

Vol 13 (4) ◽

pp. 1929

Author(s):

Yongmao Xiao ◽

Wei Yan ◽

Ruping Wang ◽

Zhigang Jiang ◽

Ying Liu

Keyword(s):

Optimization Model ◽

Optimization Design ◽

Design Method ◽

Low Cost ◽

Route Optimization ◽

Low Carbon ◽

Multi Objective Optimization ◽

Multi Objective ◽

Blank Design ◽

Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

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