scholarly journals Neutrosophic Optimization Model and Computational Algorithm for Optimal Shale Gas Water Management under Uncertainty

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 544 ◽  
Author(s):  
Firoz Ahmad ◽  
Ahmad Yusuf Adhami ◽  
Florentin Smarandache
Keyword(s):  
Water Management ◽  
Shale Gas ◽  
Optimization Model ◽  
Computational Study ◽  
Treatment Plant ◽  
Solution Procedure ◽  
Programming Approach ◽  
Underground Disposal ◽  
Management Optimization ◽  
Expansion Capacity

Shale gas energy is the most prominent and dominating source of power across the globe. The processes for the extraction of shale gas from shale rocks are very complex. In this study, a multiobjective optimization framework is presented for an overall water management system that includes the allocation of freshwater for hydraulic fracturing and optimal management of the resulting wastewater with different techniques. The generated wastewater from the shale fracking process contains highly toxic chemicals. The optimal control of a massive amount of contaminated water is quite a challenging task. Therefore, an on-site treatment plant, underground disposal facility, and treatment plant with expansion capacity were designed to overcome environmental issues. A multiobjective trade-off between socio-economic and environmental concerns was established under a set of conflicting constraints. A solution method—the neutrosophic goal programming approach—is suggested, inspired by independent, neutral/indeterminacy thoughts of the decision-maker(s). A theoretical computational study is presented to show the validity and applicability of the proposed multiobjective shale gas water management optimization model and solution procedure. The obtained results and conclusions, along with the significant contributions, are discussed in the context of shale gas supply chain planning policies over different time horizons.

Leading the City of Baltimore into the 21st Century: Flexible Treatment Solutions and Integrated Raw Water Management

2010 ◽  
Vol 5 (4) ◽  
Author(s):  
J. L. Manuszak ◽  
M. MacPhee ◽  
S. Liskovich ◽  
L. Feldsher
Keyword(s):  
Water Management ◽  
Water Quality ◽  
Water Supply ◽  
Conceptual Design ◽  
Membrane Filtration ◽  
Treatment Plant ◽  
Low Pressure ◽  
Management Tool ◽  
Raw Water ◽  
The City

The City of Baltimore, Maryland is one of many US cities faced with challenges related to increasing potable water demands, diminishing fresh water supplies, and aging infrastructure. To address these challenges, the City recently undertook a $7M study to evaluate water supply and treatment alternatives and develop the conceptual design for a new 120 million gallon per day (MGD) water treatment plant. As part of this study, an innovative raw water management tool was constructed to help model source water availability and predicted water quality based on integration of a new and more challenging surface water supply. A rigorous decision-making approach was then used to screen and select appropriate treatment processes. Short-listed treatment strategies were demonstrated through a year-long pilot study, and process design criteria were collected in order to assess capital and operational costs for the full-scale plant. Ultimately the City chose a treatment scheme that includes low-pressure membrane filtration and post-filter GAC adsorption, allowing for consistent finished water quality irrespective of which raw water supply is being used. The conceptual design includes several progressive concepts, which will: 1) alleviate treatment limitations at the City's existing plants by providing additional pre-clarification facilities at the new plant; and 2) take advantage of site conditions to design and operate the submerged membrane system by gravity-induced siphon, saving the City significant capital and operations and maintenance (O&M) costs. Once completed, the new Fullerton Water Filtration Plant (WFP) will be the largest low-pressure membrane plant in North America, and the largest gravity-siphon design in the world.

Designing a sustainable supply chain network for producing high-value products from waste glass

2021 ◽  
pp. 0734242X2199466
Author(s):  
Naeme Zarrinpoor
Keyword(s):  
Supply Chain ◽  
Greenhouse Gas Emission ◽  
Fuzzy Programming ◽  
Solution Procedure ◽  
Waste Glass ◽  
Worker Safety ◽  
Programming Approach ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Proposed Model

This paper aims to design a supply chain network for producing double glazed glass from the recycling of waste glass. All three pillars of sustainability are taken into consideration. The economic objective tries to maximize total profits. The environmental objective considers the energy consumption, the generated waste, the greenhouse gas emission, the water consumption, and the fuel consumption of vehicles. The social objective addresses created job opportunities, the worker safety, the regional development, the worker benefit, and training hours. To solve the model, a two-stage framework based on the group best-worst method and an interactive fuzzy programming approach is developed. The proposed model is validated through a real case study based on waste glass management in the city of Shiraz. It is revealed that when sustainable development goals are approached, a great degree of improvement will be attained in environmental and social aspects without a significant decrease in the economic sustainability. The results also demonstrate that the locations of glass recycling centres are different under economic, environmental, and social pillars, and the proposed model yields an optimal system configuration with a proper satisfaction degree of all objectives. Moreover, applying the proposed solution procedure enables system designers to obtain the most desirable trade-off between different aspects of sustainability.

scholarly journals Constraint Programming Approach for Optimizing Business Asset Maintenance Strategy

2019 ◽  
Vol 1 (01) ◽  
Author(s):  
Gilang Ramadhan ◽  
Shu Shun Liu
Keyword(s):  
Decision Making ◽  
Constraint Programming ◽  
Optimization Model ◽  
Maintenance Treatment ◽  
Treatment Options ◽  
Programming Approach ◽  
Building Maintenance ◽  
Maintenance Program ◽  
Building Condition ◽  
Decision Making Tool

There are many buildings with various conditions in Indonesia and some of them are not in finest conditions that need maintenance treatment urgently. The absence of building maintenance decision-making tool and limited budget are among main factors that cause unmanageable maintenance program. Therefore, this study has been conducted to propose an optimization model that is capable to determine the most appropriate building maintenance treatment. This study applied Constraint Programming (CP) approach to select the most economical maintenance treatment for a certain building and to allocate annual maintenance budget. CP-based model in this study subjects to constraint of budget and targeted level of building condition. In this study, maintenance treatment options, budget, time period, building deterioration rates, and the minimum standard of building condition were set. The model was run in IBM ILOG CPLEX Optimization Studio since the software is very efficient and effective in processing the optimization model. Furthermore, a case study was carried out to run the model involving 41 buildings in a 10-year period, and two different scenarios were conducted to examine the optimization model. The results successfully validated that the model can be a decision-making tool in selecting and prioritizing effective maintenance treatment.

A game theoretical low impact development optimization model for urban storm water management

2019 ◽  
Vol 241 ◽  
pp. 118323 ◽  
Author(s):  
Morvarid Latifi ◽  
Gholamreza Rakhshandehroo ◽  
Mohammad Reza Nikoo ◽  
Mojtaba Sadegh
Keyword(s):  
Water Management ◽  
Optimization Model ◽  
Low Impact Development ◽  
Storm Water ◽  
Storm Water Management ◽  
Urban Storm

Probabilistic Segment-linked Pavement Management Optimization Model

2002 ◽  
Vol 128 (6) ◽  
pp. 568-577 ◽  
Author(s):  
Adelino Ferreira ◽  
António Antunes ◽  
Lus Picado-Santos
Keyword(s):  
Optimization Model ◽  
Pavement Management ◽  
Management Optimization
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