Multi-objective layout optimization for sponge city by annealing algorithm and its environmental benefits analysis

2021 ◽  
Vol 66 ◽  
pp. 102706
Author(s):  
Lin She ◽  
Ming Wei ◽  
Xue-yi You
2013 ◽  
Vol 307 ◽  
pp. 161-165
Author(s):  
Hai Jin ◽  
Jin Fa Xie

A multi-objective genetic algorithm is applied into the layout optimization of tracked self-moving power. The layout optimization mathematical model was set up. Then introduced the basic principles of NSGA-Ⅱ, which is a Pareto multi-objective optimization algorithm. Finally, NSGA-Ⅱwas presented to solve the layout problem. The algorithm was proved to be effective by some practical examples. The results showed that the algorithm can spread toward the whole Pareto front, and provide many reasonable solutions once for all.


Author(s):  
Safiye Turgay

Facility layout design problem considers the departments’ physcial layout design with area requirements in some restrictions such as material handling costs, remoteness and distance requests. Briefly, facility layout problem related to optimization of the layout costs and working conditions. This paper proposes a new multi objective simulated annealing algorithm for solving of the unequal area in layout design. Using of the different objective weights are generated with entropy approach and used in the alternative layout design. Multi objective function takes into the objective function and constraints. The suggested heuristic algorithm used the multi-objective parameters for initialization. Then prefered the entropy approach determines the weight of the objective functions. After the suggested improved simulated annealing approach applied to whole developed model. A multi-objective simulated annealing algorithm is implemented to increase the diversity and reduce the chance of getting layout conditions in local optima.


2021 ◽  
Author(s):  
Sijie Tang ◽  
Jiping Jiang ◽  
Yi Zheng

<p>Practitioners usually design the plan of Sponge City construction (SCC) by combining LID facilities (e.g., rain garden, rain barrels, green roofs, and grassed swales) according to their personal experiences or general guidelines. The layout (including selection, connection and distribution area) of LID facilities is subjective, in the risk of far from optimal combination. Previous researchers have developed some LID optimization tools, which only consider the dimension and number of LIDs in a given scenario. Therefore, it is necessary to develop a flexible and extensible design tool with the support of urban hydrological model to conduct the facilities layout optimization. This study introduced a SWMM-based multi-variable and multi-objective optimization framework called CAFID (Comprehensive Assessment and Fine Design Model of Sponge City) to meet this end. The assessment module with multi-objective couples diverse controlling end-points (e.g., total runoff, peak runoff, pollutant concentration, cost, and customized social-ecological factors) as the candidates of assessment criteria. The optimization module with multi-variable is implemented by SWMM, starting with three steps: 1) Full allocation. Based on the availability, list the candidates of LID facility for each sub-catchment; 2) Full connection. Order the potential stream direction of surface runoff from rainfall to municipal network, based on possible hierarchical structure of sub-catchments and LID facilities; 3) Full coverage. Identify all the suitable area for LID facility in sub-catchment. The optimization on the 3 variables, the selection, connection, and area, is powered by NSGA-II and TOPSIS algorithms, which make it possible that we choose a final result from the set of nondominated solutions according to special weight distribution. The effectiveness of CAFID was illustrated through a case of Sponge City in Fenghuangcheng of Shenzhen City, one of 30 national pilot sponge cities in China. As well, this new framework is expected to be widely verified and applied in Sponge City construction in China or similar concepts all over the world.</p>


Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4381
Author(s):  
Yan Xu ◽  
Jianhao Zhang

Regional integrated energy site layout optimization involves multi-energy coupling, multi-data processing and multi-objective decision making, among other things. It is essentially a kind of non-convex multi-objective nonlinear programming problem, which is very difficult to solve by traditional methods. This paper proposes a decentralized optimization and comprehensive decision-making planning strategy and preprocesses the data information, so as to reduce the difficulty of solving the problem and improve operational efficiency. Three objective functions, namely the number of energy stations to be built, the coverage rate and the transmission load capacity of pipeline network, are constructed, normalized by linear weighting method, and solved by the improved p-median model to obtain the optimal value of comprehensive benefits. The artificial immune algorithm was improved from the three aspects of the initial population screening mechanism, population updating and bidirectional crossover-mutation, and its performance was preliminarily verified by test function. Finally, an improved artificial immune algorithm is used to solve and optimize the regional integrated energy site layout model. The results show that the strategies, models and methods presented in this paper are feasible and can meet the interest needs and planning objectives of different decision-makers.


Sign in / Sign up

Export Citation Format

Share Document