scholarly journals Multi Criteria Governmental Crop Planning Problem: An Analytic Hierarchy Approach

Management ◽  
2012 ◽  
Vol 2 (4) ◽  
pp. 96-105 ◽  
Author(s):  
Salah R. Agha. Latifa G. Nofal ◽  
Hana A. Nassar ◽  
Rania Y. Shehada
Keyword(s):  
Planning Problem ◽  
Analytic Hierarchy ◽  
Crop Planning

scholarly journals A Model for Urban Environment and Resource Planning Based on Green GDP Accounting System

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Linyu Xu ◽  
Bing Yu ◽  
Wencong Yue ◽  
Xiaodong Xie
Keyword(s):  
Urban Environment ◽  
Energy Use ◽  
Resource Planning ◽  
Planning Problem ◽  
Accounting System ◽  
Analytic Hierarchy ◽  
Urban Economic Development ◽  
Long Run ◽  
Green Gdp ◽  
Key Factor

The urban environment and resources are currently on course that is unsustainable in the long run due to excessive human pursuit of economic goals. Thus, it is very important to develop a model to analyse the relationship between urban economic development and environmental resource protection during the process of rapid urbanisation. This paper proposed a model to identify the key factors in urban environment and resource regulation based on a green GDP accounting system, which consisted of four parts: economy, society, resource, and environment. In this model, the analytic hierarchy process (AHP) method and a modified Pearl curve model were combined to allow for dynamic evaluation, with higher green GDP value as the planning target. The model was applied to the environmental and resource planning problem of Wuyishan City, and the results showed that energy use was a key factor that influenced the urban environment and resource development. Biodiversity and air quality were the most sensitive factors that influenced the value of green GDP in the city. According to the analysis, the urban environment and resource planning could be improved for promoting sustainable development in Wuyishan City.

scholarly journals Three New Stochastic Local Search Metaheuristics for the Annual Crop Planning Problem Based on a New Irrigation Scheme

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Sivashan Chetty ◽  
Aderemi Oluyinka Adewumi
Keyword(s):  
Local Search ◽  
Agricultural Land ◽  
Absolute Difference ◽  
Planning Problem ◽  
Stochastic Local Search ◽  
Irrigation Scheme ◽  
Crop Planning ◽  
Annual Crop ◽  
Agricultural Planning ◽  
Metaheuristic Techniques

Annual Crop Planning (ACP) is an NP-hard-type optimization problem in agricultural planning. It involves finding optimal solutions concerning the seasonal allocations of a limited amount of agricultural land amongst the various competing crops that are required to be grown on it. This study investigates the effectiveness of employing three new local search (LS) metaheuristic techniques in determining solutions to an ACP problem at a new Irrigation Scheme. These three new LS metaheuristic techniques are the Best Performance Algorithm (BPA), Iterative Best Performance Algorithm (IBPA), and the Largest Absolute Difference Algorithm (LADA). The solutions determined by these LS metaheuristic techniques are compared against the solutions of two other well-known LS metaheuristic techniques in the literature. These techniques are Tabu Search (TS) and Simulated Annealing (SA). The comparison with TS and SA was to determine the relative merits of the solutions found by BPA, IBPA, and LADA. The results show that TS performed as the overall best. However, LADA determined the best solution that was the most economically feasible.

A Crop Planning Problem with Fuzzy Random Profit Coefficients

2005 ◽  
Vol 4 (1) ◽  
pp. 51-69 ◽  
Author(s):  
Tasuku Toyonaga ◽  
Takesh Itoh ◽  
Hiroaki Ishii
Keyword(s):  
Planning Problem ◽  
Crop Planning ◽  
Fuzzy Random

scholarly journals An Improved Differential Evolution Algorithm for Crop Planning in the Northeastern Region of Thailand

2018 ◽  
Vol 23 (3) ◽  
pp. 40 ◽  
Author(s):  
Udompong Ketsripongsa ◽  
Rapeepan Pitakaso ◽  
Kanchana Sethanan ◽  
Tassin Srivarapongse
Keyword(s):  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Optimal Solution ◽  
Computational Time ◽  
Planning Problem ◽  
Selling Price ◽  
Neighborhood Structure ◽  
Crop Planning ◽  
Improved Differential Evolution Algorithm

This research aimed to solve the economic crop planning problem, considering transportation logistics to maximize the profit from cultivated activities. Income is derived from the selling price and production rate of the plants; costs are due to operating and transportation expenses. Two solving methods are presented: (1) developing a mathematical model and solving it using Lingo v.11, and (2) using three improved Differential Evolution (DE) Algorithms—I-DE-SW, I-DE-CY, and I-DE-KV—which are DE with swap, cyclic moves (CY), and K-variables moves (KV) respectively. The algorithms were tested by 16 test instances, including this case study. The computational results showed that Lingo v.11 and all DE algorithms can find the optimal solution eight out of 16 times. Regarding the remaining test instances, Lingo v.11 was unable to find the optimal solution within 400 h. The results for the DE algorithms were compared with the best solution generated within that time. The DE solutions were 1.196–1.488% better than the best solution generated by Lingo v.11 and used 200 times less computational time. Comparing the three DE algorithms, MDE-KV was the DE that was the most flexible, with the biggest neighborhood structure, and outperformed the other DE algorithms.

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