MULTI-RESERVOIR OPERATION BY ADAPTIVE PHEROMONE RE-INITIATED ANT COLONY OPTIMIZATION ALGORITHM

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

JALALI M.R.; AFSHAR A.; MARINO M.A.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: INTERNATIONAL JOURNAL OF CIVIL ENGINEERING Year:2007 | Volume:5 | Issue:4 Page(s): 284-301

Download Full-Text

View:

419

Download:

407

Cites:

Information Journal Paper

Title

MULTI-RESERVOIR OPERATION BY ADAPTIVE PHEROMONE RE-INITIATED ANT COLONY OPTIMIZATION ALGORITHM

Author(s)

JALALI M.R. | AFSHAR A. | MARINO M.A. | Issue Writer Certificate

Keywords

ANT COLONY

OPTIMIZATION

RESERVOIR OPERATION

MULTI-RESERVOIR

Abstract

Through a collection of cooperative agents called ants, the near optimal solution to the MULTI-RESERVOIR operation problem may be effectively achieved employing ANT COLONY OPTIMIZATION Algorithms (ACOAs). The problem is approached by considering a finite operating horizon, classifying the possible releases from the reservoir(s) intopre-determined intervals, and projecting the problem on a graph. By defining an optimality criterion, the combination of desirable releases from the reservoirs or operating policy is determined. To minimize the possibility of premature convergence to a local optimum, a combination of Pheromone Re-Initiation (PRI) and Partial Path Replacement (PPR) mechanisms are presented and their effects have been tested in a benchmark, nonlinear, and multimodal mathematical function. The finalized model is then applied to develop an optimum operatingpolicy for a single reservoir and a benchmark four-reservoir operation problem. Integration of these mechanisms improves the final result, as well as initial and final rate of convergence. In the benchmark Ackley function minimization problem, after 410 iterations, PRI mechanism improved the final solution by 97 percent and the combination of PRI and PPR mechanisms reduced final result to global optimum. As expected in the single-reservoir problem, with a continuous search space, a nonlinear programming (NLP) approach performed better than ACOAs employing a discretized search space on the decision variable (reservoir release). As the complexity of the system increases, the definition of an appropriate heuristic function becomes more and more difficult; this may provide wrong initial sight or vision to the ants. By assigning a minimum weight to the exploitation term in a transition rule, the best result is obtained. In a benchmark 4-reservoirproblem, a very low standard deviation is achieved for 10 different runs and it is considered as an indication of low diversity of the results. In 2 out of 10 runs, the global optimal solution is obtained, where in the other 8 runs; results are as close as 99.8 percent of the global solution. Results and execution time compare well with those of well developed genetic algorithms (GAs).

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

JALALI, M.R., AFSHAR, A., & MARINO, M.A.. (2007). MULTI-RESERVOIR OPERATION BY ADAPTIVE PHEROMONE RE-INITIATED ANT COLONY OPTIMIZATION ALGORITHM. INTERNATIONAL JOURNAL OF CIVIL ENGINEERING, 5(4), 284-301. SID. https://sid.ir/paper/271771/en

Vancouver: Copy

JALALI M.R., AFSHAR A., MARINO M.A.. MULTI-RESERVOIR OPERATION BY ADAPTIVE PHEROMONE RE-INITIATED ANT COLONY OPTIMIZATION ALGORITHM. INTERNATIONAL JOURNAL OF CIVIL ENGINEERING[Internet]. 2007;5(4):284-301. Available from: https://sid.ir/paper/271771/en

IEEE: Copy

M.R. JALALI, A. AFSHAR, and M.A. MARINO, “MULTI-RESERVOIR OPERATION BY ADAPTIVE PHEROMONE RE-INITIATED ANT COLONY OPTIMIZATION ALGORITHM,” INTERNATIONAL JOURNAL OF CIVIL ENGINEERING, vol. 5, no. 4, pp. 284–301, 2007, [Online]. Available: https://sid.ir/paper/271771/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops