A STOCHASTIC SIMULATION-BASED HYBRID INTERVAL FUZZY PROGRAMMING APPROACH FOR OPTIMIZING THE TREATMENT OF RECOVERED OILY WATER

Jing, Liang and Chen, Bing and Zhang, Baiyu and Pu, Li (2012) A STOCHASTIC SIMULATION-BASED HYBRID INTERVAL FUZZY PROGRAMMING APPROACH FOR OPTIMIZING THE TREATMENT OF RECOVERED OILY WATER. The Journal of Ocean Technology, 7 (4). pp. 59-72. ISSN 1718-3200

[img] [English] PDF (Migrated (PDF/A Conversion) from original format: (application/pdf)) - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (872Kb)

Abstract

In this paper, a stochastic simulation-based hybrid interval fuzzy programming (SHIFP) approach is developed to aid the decision-making process by solving fuzzy linear optimization problems. Fuzzy set theory, probability theory, and interval analysis are integrated to take into account the effect of imprecise information, subjective judgment, and variable environmental conditions. A case study related to oily water treatment during offshore oil spill clean-up operations is conducted to demonstrate the applicability of the proposed approach. The results suggest that producing a random sequence of triangular fuzzy numbers in a given interval is equivalent to a normal distribution when using the centroid defuzzification method. It also shows that the defuzzified optimal solutions follow the normal distribution and range from 3,000-3,700 tons, given the budget constraint (CAD 110,000-150,000). The normality seems to be able to propagate throughout the optimization process, yet this interesting finding deserves more in-depth study and needs more rigorous mathematical proof to validate its applicability and feasibility. In addition, the optimal decision variables can be categorized into several groups with different probability such that decision makers can wisely allocate limited resources with higher confidence in a short period of time. This study is expected to advise the industries and authorities on how to distribute resources and maximize the treatment efficiency of oily water in a short period of time, particularly in the context of harsh environments.

Item Type: Article
URI: http://research.library.mun.ca/id/eprint/677
Item ID: 677
Keywords: Simulation-based hybrid interval fuzzy programming; Fuzzy linear optimization; Oil spill clean-up; Recovered oily water
Department(s): Engineering and Applied Science, Faculty of
Date: 2012
Date Type: Publication

Actions (login required)

View Item View Item

Downloads

Downloads per month over the past year

View more statistics