Simulation–optimization method based on rationality evaluation for waste load allocation in Daliao river

2015 ◽  
Vol 73 (9) ◽  
pp. 5193-5209 ◽  
Author(s):  
Kun Lei ◽  
Gang Zhou ◽  
Fu Guo ◽  
Soon-Thiam Khu ◽  
Guangjun Mao ◽  
...  
Keyword(s):  
Simulation Optimization ◽  
Optimization Method ◽  
Waste Load Allocation ◽  
Waste Load

scholarly journals Waste load allocation under uncertainty using game theory approach and simulation-optimization process

2020 ◽  
Vol 22 (4) ◽  
pp. 815-841 ◽  
Author(s):  
Behnam Andik ◽  
Mohammad Hossein Niksokhan
Keyword(s):  
Game Theory ◽  
Sensitivity Analysis ◽  
Simulation Optimization ◽  
Graph Model ◽  
Decision Makers ◽  
Optimization Process ◽  
Theory Approach ◽  
Waste Load Allocation ◽  
Waste Load ◽  
The Status

Abstract This article aims to present a new methodology for waste load allocation (WLA) in a riverine system considering the uncertainty and achieve the lowest amount of inequity index, cost, and fuzzy risk of standard violation. To find a surface of undominated solutions, a new modified PAWN method, initially designed for sensitivity analysis, was developed and coupled with a simulation-optimization process using multi-objective particle swarm optimization (MOPSO) algorithm, to consider the uncertainty of all affecting variables and parameters by using their probability distribution. The proposed methodology applied to Sefidrood River in the northern part of Iran. Graph model for conflict resolution (GMCR) as a subset of game theory was implemented to attain a compromise on WLA among the stakeholders of a river system's quality in Iran: Department of Environment, Municipal Waste Water, and Private Sector. Some undominated solutions were used in GMCR model and modeling the conflict among decision makers reveals that their preferences and the status quo do not lead to a solely stable equilibrium; thus the intervention of a ruler as arbitrator leads them to reach a compromise on a scenario that has a median FRVS and cost. Sensitivity analysis was done using the PAWN method to assess the sensitivity of three intended objectives to all variables and parameters.

Heuristic Algorithms for Waste Load Allocation in a River Basin

1989 ◽  
Vol 21 (8-9) ◽  
pp. 1057-1064 ◽  
Author(s):  
Vijay Joshi ◽  
Prasad Modak
Keyword(s):  
Dynamic Programming ◽  
Heuristic Algorithms ◽  
Water Quality Management ◽  
User Preferences ◽  
Theory And Practice ◽  
Waste Load Allocation ◽  
Practical Applications ◽  
Waste Load ◽  
On Line ◽  
The One

Waste load allocation for rivers has been a topic of growing interest. Dynamic programming based algorithms are particularly attractive in this context and are widely reported in the literature. Codes developed for dynamic programming are however complex, require substantial computer resources and importantly do not allow interactions of the user. Further, there is always resistance to utilizing mathematical programming based algorithms for practical applications. There has been therefore always a gap between theory and practice in systems analysis in water quality management. This paper presents various heuristic algorithms to bridge this gap with supporting comparisons with dynamic programming based algorithms. These heuristics make a good use of the insight gained in the system's behaviour through experience, a process akin to the one adopted by field personnel and therefore can readily be understood by a user familiar with the system. Also they allow user preferences in decision making via on-line interaction. Experience has shown that these heuristics are indeed well founded and compare very favourably with the sophisticated dynamic programming algorithms. Two examples have been included which demonstrate such a success of the heuristic algorithms.

A simulation–optimization method: Its convergence and utility

1983 ◽  
Vol 30 (2) ◽  
pp. 227-236 ◽  
Author(s):  
Guy L. Curry ◽  
Darald J. Hartfiel
Keyword(s):  
Simulation Optimization ◽  
Optimization Method

Research on Human and Vehicles Coordination Evacuation Simulation Optimization Method under Emergency Incidents

2011 ◽  
Vol 71-78 ◽  
pp. 3091-3096
Author(s):  
Yun Long Ma ◽  
Jian Wang
Keyword(s):  
Ant Colony Algorithm ◽  
Simulation Optimization ◽  
Optimization Method ◽  
Emergency Planning ◽  
Optimal Scheduling ◽  
Regular Pattern ◽  
Improved Genetic Algorithm ◽  
Evacuation Simulation ◽  
Evacuation Strategy ◽  
Coordination System

Among researches on crowd flow evacuation under emergency, there are no deep touch of coordinating evacuation strategy of crowd and traffic, and also can not set models and simulate the whole picture of evacuation. The purpose of this research is to realize the coordinating evacuation of both traffic and crowd. The author divided the situations into Not Intervene and May Intervene, analyzed the coordination system and probed the model of coordinating evacuation. A series of coordinate evacuation method has been put forward based on swarm intelligence and simulation optimization. Based on the result of crowd simulation and Ant colony algorithm, in order to find the optimal traffic evacuation proposal, the author took use of the improved Genetic Algorithm as well as the distributed coordinating simulation, finally found a systematic optimal scheduling program. Also the internal regular pattern of coordinating evacuation has also been revealed. All these will provide support for emergency planning and decision making.

Sign in / Sign up

Export Citation Format

Share Document