Optimal Planning of Asian Expressway Network Without Dynamic Interregional Input–Output Programming Model

Author(s):  
Hirotada Kohno ◽  
Yoshiro Higano
2019 ◽  
pp. 12-25
Author(s):  
Jidong Kang ◽  
Tsan Sheng Ng

The current paper combines multi-regional input-output model and linear programming model to identify industrial shift strategies for CO2 emissions reduction in China. As a supplement to the previous studies, the optimal sequence of demand regulation for various products is explored. The results show that demand side regulation would pose negative effect on both GDP and CO2 emissions. However, certain strategies can be adopted to decrease CO2 emissions at the minimum decrease in GDP. According to the optimal sequence analysis, a group of key final products, such as the metallurgy products, the nonmetal products, the metal products, and the chemical products should be firstly regulated. Most of these key products concentrate in the eastern and coastal regions in China. Our model can be used to aid policy makers in design of effective industrial restructuring policy to achieve the national emissions targets.


2011 ◽  
Vol 339 ◽  
pp. 358-361
Author(s):  
Guo Li Liu ◽  
Jun Zhao ◽  
Wei Wang

This paper deals with the product blending problem originating from the production system of a large typical oil refinery. A deterministic mixed integer programming model is proposed. The objective is to make an effective production-inventory plan for product blending unit (PBU) in order to meet the demand of product oil with no backlogging allowed and minimize the total costs, that is, the sum of purchasing, production, inventory and setup costs. The constraints related to material balance, different capacities and different production schemes are considered. A numerical example is subsequently provided to illustrate the broad applicability of the proposed model.


1995 ◽  
Vol 43 (1) ◽  
pp. 47-59
Author(s):  
J. Bessembinder

The problem of uncertainties in input-output coefficients is examined, using the uncertainty in estimating the fertilizer use efficiency as an illustration. An example of uncertainty due to lack of knowledge on processes involved is the use of different approaches for estimating fertilizer use efficiency in two land use optimization studies. A further problem is uncertainty due to lack of data; this is illustrated with an example from the Atlantic Zone of Costa Rica. Very few data are available to determine fertilizer use efficiency and data from regions with similar soil and climate type are not available. Data from non-similar regions may not give a correct assessment of the possibilities in the region. Different concepts and sources of information result in different estimates of coefficients, which might in turn greatly influence the results of the linear programming model. It is therefore concluded that, rather than using one fixed value for a particular input-output coefficient, the effect of uncertainty in coefficients on the final results of the model should be examined.


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