An interval multi-objective fuzzy-interval credibility-constrained nonlinear programming model for balancing agricultural and ecological water management

2022 ◽  
pp. 103958
Author(s):  
Qi Pan ◽  
Chenglong Zhang ◽  
Shanshan Guo ◽  
Hanshi Sun ◽  
Jiayu Du ◽  
...  
Keyword(s):  
Water Management ◽  
Nonlinear Programming ◽  
Programming Model ◽  
Multi Objective ◽  
Nonlinear Programming Model ◽  
Constrained Nonlinear Programming ◽  
Fuzzy Interval

Research on the Optimized Configuration of Water Resource in Shendong Mining Area

2014 ◽  
Vol 1073-1076 ◽  
pp. 1669-1672
Author(s):  
Bao Feng Zhao
Keyword(s):  
Nonlinear Programming ◽  
Water Resource ◽  
Programming Model ◽  
Water Shortage ◽  
Mining Area ◽  
Water Diversion ◽  
Resource Exploitation ◽  
Multi Objective ◽  
Nonlinear Programming Model ◽  
Mining Water

In order to improve water resource utilization and protect ecological environment in Shendong mining area, make the coal and water resource developed healthy. The multi-objective nonlinear programming model of water resources in mining area was established based on LINGO platform, the optimized configuration of water resource was researched. According to the result of model calculation, based on the optimized configuration of water resource and coal mining in 2012, 2015 and 2020, there are different levels of water shortage. The total water deficit is-526.56、-1189.37 and-1642.30 104m3. According to the actual situation and calculation result, the proposal is put forward in improving the utilization ratio of mining water, water diversion from external and flood utilization. The optimized configuration of water resource in Shendong mining area based on multi-objective nonlinear programming is scientifically, rationally, and plays a guiding role in harmonious development between coal resource exploitation and utilization of water resource.

A mixed integer nonlinear programming model for optimal design of natural gas storage surface double-pipe network

2021 ◽  
Vol 44 ◽  
pp. 103379
Author(s):  
Jun Zhou ◽  
Tiantian Fu ◽  
Yulin Chen ◽  
Yao Xiao ◽  
Jinghong Peng ◽  
...  
Keyword(s):  
Nonlinear Programming ◽  
Optimal Design ◽  
Natural Gas ◽  
Programming Model ◽  
Gas Storage ◽  
Mixed Integer ◽  
Pipe Network ◽  
Integer Nonlinear Programming ◽  
Nonlinear Programming Model ◽  
Double Pipe

A Bi-objective Multi-Product Multi-Constraint EPQ Model in a Stochastic Environment and Partial Shortage

2020 ◽  
Vol 19 (03) ◽  
pp. 567-587
Author(s):  
Seyedeh Sanaz Mirkhorsandi ◽  
Seyed Hamid Reza Pasandideh
Keyword(s):  
Goal Attainment ◽  
Programming Model ◽  
Multi Objective ◽  
Holding Costs ◽  
Inventory Costs ◽  
Economic Production ◽  
Proposed Model ◽  
Demand Rate ◽  
Nonlinear Programming Model ◽  
Epq Model

One of the classical models for inventory control is economic production quantity (EPQ), which is widely used in industry. In this paper, an EPQ model with partial shortage is developed by considering the real world conditions, and costs related to the backorder demand are taken as fixed and time-dependent. In the proposed model, determination of the inventory cycle length, the length of positive inventory cycle and backordered demand rate are considered in shortage period. The aim of the presented research is to minimize the total inventory costs and the space required for storage products so that the stochastic and classic constraints including holding costs, lost sales, backorder, budget, total number of productions and average shortage times should be satisfied while optimizing the multi-objective problem. Presented model is a bi-objective nonlinear programming model. Then, to solve the proposed model, three multi-objective decision-making methods including Lp-metric, goal programming and goal attainment are used. Besides, numerical examples are executed in small, medium and large scales by use of GAMS software, and the performance of the methods is compared in terms of objective functions and required CPU time. Finally, sensitivity analysis is done to determine the effect of change in the main parameters of the model on the objective function value.

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