Convergence of a Single Run Simulation Optimization Algorithm

1988 ◽  
Author(s):  
Ying Tat Leung ◽  
Rajan Suri
1989 ◽  
Vol 16 (4) ◽  
pp. 477-482 ◽  
Author(s):  
Kim D. Barlishen ◽  
Slobodan P. Simonovic ◽  
Donald H. Burn

A simultion–optimization algorithm for sizing potential reservoirs on a river basin has been used to demonstrate the effects of the streamflow record length on capacity requirements. The sizing procedure involves the generation of synthetic streamflows and a reservoir reliability analysis. Two levels of reliability are present: the reliability in meeting water supply requirements, and the probability level associated with the final capacity selection. The procedure was applied to synthetic sequences generated from an 81-year inflow record and subsets of this sequence to produce frequency distributions of required capacities. The capacities with a 5% probability of exceedence were compared. Relying on short inflow sequences can lead to substantial overestimations or underestimations of capacity. A key factor is the presence of the critical period in the analysis. An open question remains regarding the effect of the final probability level selection on the range of capacities observed. Key words: design reservoirs, water supply, simulation, optimization, reliability, record length, synthetic streamflows.


2020 ◽  
Vol 17 (9) ◽  
pp. 4612-4622
Author(s):  
Priyanka Chugh ◽  
Dinesh Rai ◽  
S. Indu

Wireless and mobile devices and networks are an integral part of today’s life. With the advancement of technology, a large number of smart devices with advanced computational and communicational types of equipment are designed and developed. With these advancements, the availability of services over these devices is required to be of high quality for ensuring better experiences day by day. Thus, network performance improvement with minimum path loss and optimized packet delivery without loops is a major concern to integrate the existing network infrastructure with advanced and future networks. This work has designed a novel route deviation and optimization algorithm with simulation optimization and energy efficiency constraints. The simulation-optimization approach is considered to have minimum link losses and avoid the loop problem. Whereas, local and global simulation optimization processes are followed to identify the best possibilities in route identification in consideration with local and network environment settings. The proposed approach is statistically found to have a minimum error rate and optimizes the performance with computational and communicational overheads. In results, a minimum of 10 seconds and a maximum of 150 seconds are observed before a device using the proposed approach gets utilized fully. Thus, the proposed approach is very effective for link loss and loop problems in wireless sensor networks. Further, an improvement of 135 (approx.) is observed in the proposed approach.


2009 ◽  
Vol 12 (2) ◽  
pp. 212-224 ◽  
Author(s):  
H. Abbasi ◽  
A. Afshar ◽  
M. R. Jalali

Valve and pump shut-off in water pipeline systems lead to transient flow. This flow is a complex phenomenon and is potentially a very serious problem causing extra dynamic pressure in the system. Within the last few decades, the evolutionary and meta-heuristic algorithms, such as genetic algorithms, simulated annealing. More recently, however, ant-colony optimization algorithms have received considerable attention. In this paper the procedure and application of the ant-colony optimization algorithm to the design of a water supply pipeline system, considering dynamic pressures arising from valve closure, is presented. A simulation–optimization interaction loop (SOIL) is defined that cycles between the steady-state and transient flow modules to describe the hydraulics of the pipeline and ant colony optimization algorithm. A hydraulic simulation module is coupled with the ant colony optimization algorithm to form an efficient and powerful software program which locates the pumping stations at any possible or predefined locations while optimizing their specifications, along with pipe diameters, at each decision point. The model may equally regard or disregard the dynamic pressures. Two examples are provided to illustrate the proposed methodology which is limited to the solution of any gravity and/or forced water supply pipeline which is typical for water supply systems.


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