Multiobjective Optimization Model of Production Planning in Cloud Manufacturing Based on TOPSIS Method with Combined Weights

Combined with the research of mass customization and cloud manufacturing mode, this paper discussed the production planning of mass customization enterprises in the context of cloud manufacturing in detail, analyzed the attribute index of manufacturing resource combination, and given a system considering the characteristics of batch production in mass customization and the decentralization of manufacturing resources in cloud manufacturing environment. Then, a multiobjective optimization model has been constructed according to the product delivery date, product cost, and product quality that customers care most about. The Pareto solution set of production plan has been obtained by using NSGA-II algorithm. This paper established a six-tier attribute index system evaluation model for the optimization of production planning scheme set of mass customization enterprises in cloud manufacturing environment. The weight coefficients of attribute indexes were calculated by combining subjective and objective weights with analytic hierarchy process (AHP) and entropy weight method. Finally, the combined weights calculated were applied to the improved TOPSIS method, and the optimal production planning scheme has been obtained by ranking. This paper validated the effectiveness and feasibility of the multiobjective model and NSGA-II algorithm by the example of company A. The Pareto effective solution has been obtained by solving the model. Then the production plan set has been sorted synthetically according to the comprehensive evaluation model, and the optimal production plan has been obtained.

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Research of the Optimal Production Planning Based on Multi-Group

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.263-266.3490 ◽

2012 ◽

Vol 263-266 ◽

pp. 3490-3495

Author(s):

Shu Di Wei ◽

Hui Huang Zhao

Keyword(s):

Production Planning ◽

Production Plan ◽

Linear Programming Method ◽

Optimal Production ◽

Production Program ◽

Maximum Profit ◽

Optimal Population ◽

Definition Of ◽

The Cost ◽

Population Program

In the case of limited resources, we do not only need to think how to develop a production plan to best meet the needs of different groups, but we also gain maximum profits. That means how to make the decision for the actual production. According to the cost of production planning, the resource producer can gain maximum profit. Based on a thorough research in this issue, we state a formal definition of the multi-group multi-program multi-attribute problems, propose the optimal population program decisions with Topsis, and use a linear programming method to develop the optimal production program .The experiment results validate that the method is feasible.

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Determination of Optimal Production Number by Considering the Use of Raw Materials Using Goal Programming Approach

Computer Engineering and Applications Journal ◽

10.18495/comengapp.v7i3.263 ◽

2018 ◽

Vol 7 (3) ◽

Author(s):

Ikhsan Siregar

Keyword(s):

Production Planning ◽

Goal Programming ◽

Raw Materials ◽

Programming Method ◽

Programming Approach ◽

Production Plan ◽

Optimal Production ◽

Good Production ◽

Actual Method

The company produces PVC pipes in Medan city is experiencing problems in the form of a higher number of requests compared to the production number. This is because the company does not have a good production plan which is the results in not meeting consumer demand. For this reason, a good and integrated production planning is needed by using the goal programming method. Production planning carried out with goal programming aims to maximize company profits. The results shows that by using the goal programming method, the optimal production number was obtained at each type of 2-inch ECO JIS D pipe products of 42851 units, 3-inch ECO JIS D pipe products of 54445 units and 4 inches of ECO JIS D pipe products 24480 units. In addition, by using this method the company profits about Rp. 446,620,100 is greater than the actual method applied by the company.

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A utility-aware multi-task scheduling method in cloud manufacturing using extended NSGA-II embedded with game theory

International Journal of Computer Integrated Manufacturing ◽

10.1080/0951192x.2020.1858502 ◽

2021 ◽

pp. 1-20

Author(s):

Wenyu Zhang ◽

Jiuhong Xiao ◽

Shuai Zhang ◽

Jian Lin ◽

Ruijun Feng

Keyword(s):

Game Theory ◽

Task Scheduling ◽

Cloud Manufacturing ◽

Nsga Ii ◽

Scheduling Method

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Evaluation of subway passengers transfer hub congestion based on queuing model and TOPSIS method

Journal of Computational Methods in Sciences and Engineering ◽

10.3233/jcm-215101 ◽

2021 ◽

pp. 1-22

Author(s):

Xiaokun Wang ◽

Dong Ni

Keyword(s):

Queuing Theory ◽

Evaluation Model ◽

Flow Characteristics ◽

Distribution Area ◽

Flow Density ◽

Topsis Method ◽

Queuing Model ◽

Service Facility ◽

Passenger Flow ◽

Topsis Technique

To scientifically and reasonably evaluate and pre-warn the congestion degree of subway transfer hub, and effectively know the risk of subway passengers before the congestion time coming. We analyzed the passenger flow characteristics of various service facilities in the hub. The congested area of the subway passenger flow interchange hub is divided into queuing area and distribution area. The queuing area congestion evaluation model selects M/M/C and M/G/C based on queuing theory. The queuing model and the congestion evaluation model of the distribution area select the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. Queue length and waiting time are selected as the evaluation indicators of congestion in the queuing area, and passenger flow, passenger flow density and walking speed are selected as the evaluation indicators of congestion in the distribution area. And then, K-means cluster analysis method is used to analyze the sample data, and based on the selected evaluation indicators and the evaluation model establishes the queuing model of the queuing area and the TOPSIS model of the collection and distribution area. The standard value of the congestion level of various service facilities and the congestion level value of each service facility obtained from the evaluation are used as input to comprehensively evaluate the overall congestion degree of the subway interchange hub. Finally we take the Xi’an Road subway interchange hub in Dalian as empirical research, the data needed for congestion evaluation was obtained through field observations and questionnaires, and the congestion degree of the queue area and the distribution area at different times of the workday was evaluated, and the congestion of each service facility was evaluated. The grade value is used as input, and the TOPSIS method is used to evaluate the degree of congestion in the subway interchange hub, which is consistent with the results of passenger congestion in the questionnaire, which verifies the feasibility of the evaluation model and method.

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