A multi-stakeholder framework for urban runoff quality management: Application of social choice and bargaining techniques

Ghodsi, Seyed Hamed; Kerachian, Reza; Zahmatkesh, Zahra

doi:10.1016/j.scitotenv.2016.01.052

Cited by 65 publications

(12 citation statements)

References 21 publications

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“…4. Pairwise comparisons voting, PC, match alternatives with each other head-to-head (Srdjevic, 2007;Ghodsi et al, 2016). Each alternative gets 1 point for a one-on-one win and a half a point for a tie.…”

Section: Voting Methodsmentioning

confidence: 99%

Water Allocation Management Under Scarcity: A Bankruptcy Approach

Zheng

Sang

Liu

et al. 2022

Preprint

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This study hopes to develop multi-criteria decision making (MCDM) method for equitable and efficient allocation water resource under scarcity. Based on the Bankruptcy problems, five classic plus one proposed allocation rules are introduced to generate water distribution alternatives. The "Core" solution of Cooperative Game Theory (CGT) and Security Restriction have been used to select the feasible alternatives. Additionally, five voting methods in Social Choice Theory (SCT) are launched to aggregate preferences and obtain "win" alternative. Apply this model on 2030 water allocation management project of Ezhou City, China, as a case study. Under the proposed rule, adjust minimal overlap rule (AMO), five regions, Urban Area, Gedian DZ and three counties, hold the water deficit rate of 5.9%, 15.8% and 4.7%-6.1%, respectively. By voting technique, AMO wins four fifths of aggregating processes and came in the second for the last, which provides some insights for allocating water in a fair and feasible way.

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Section: Voting Methodsmentioning

confidence: 99%

Water Allocation Management Under Scarcity: A Bankruptcy Approach

Zheng

Sang

Liu

et al. 2022

Preprint

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“…Wang et al ( 18 ) provide a summary of methods on how to incorporate preferences into multi-objective optimization (MOO), such as weight sum method, reference point, reference direction, utility function, and so forth. According to Coello et al ( 19 ), preference-based MOO approaches are divided into three categories: priori ( 20 , 21 ), progressive ( 22 , 23 ), and posteriori ( 24 ) preference articulations, which mean making decisions before, during, and after search, respectively. In ST, it may be impractical for a decision-maker (DM) to specify their preferences completely before any alternatives are known.…”

Section: Literature Reviewmentioning

confidence: 99%

Preference-Based Multi-Objective Optimization for Synchromodal Transport Using Adaptive Large Neighborhood Search

Zhang

Atasoy

Negenborn

2021

Transportation Research Record: Journal of the Transportation R

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Decision-makers in synchromodal transport (ST) have different preferences toward different objectives, such as cost, time, and emissions. To solve the conflicts among objectives and obtain preferred solutions, a preference-based multi-objective optimization model is developed. In ST, containers need to be transferred across modes, therefore the optimization problem is formulated as a pickup and delivery problem with transshipment. The preferences of decision-makers are usually expressed in linguistic terms, so weight intervals, that is, minimum and maximum weights, are assigned to objectives to represent such vague preferences. An adaptive large neighborhood search is developed and used to obtain non-dominated solutions to construct the Pareto frontier. Moreover, synchronization is an important feature of ST and it makes available resources fully utilized. Therefore, four synchronization cases are identified and studied to make outgoing vehicles cooperate with changes of incoming vehicles’ schedules at transshipment terminals. Case studies in the Rhine-Alpine corridor are designed and the results show that the proposed approach provides non-dominated solutions which are in line with preferences. Moreover, the mode share under different preferences is analyzed, which signals that different sustainability policies in transportation will influence the mode share.

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“…LID is planned to be able to filter waste, control the flood water level, the volume of floodwater that will be released into the downstream area and maintain the base flow. There are several types of LID, including [10]:  Bio-retention cell, which is a technology that combines plant elements in a landscape with a layer of gravel to maximize water absorption into the soil.  The rain garden, which is a type of bio-retention cell that only uses a layer of soil without using a layer of gravel beneath it.…”

Section: Lid (Low Impact Development)mentioning

confidence: 99%

Low Impact Development (LID) as an effort to achieve a sustainable urban drainage system (SUDS). Case Study: Left Side Of Garang River Segment VI Semarang

2019

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The Garang River functions as a flood controller and a source of raw water for drinking water. This river is divided into seven segments, and in the downstream segment VI there is intake of raw water for drinking water. The land use is dominated by built-in land, in the form of dense settlements and industrial estates. This study aims to evaluate the condition of the drainage system, both in terms of runoff and water quality, and apply the concept of LID to achieve a sustainable drainage system. The method used is the SWMM. Evaluations were carried out in three outlets. In existing conditions, channel capacity in general is still sufficient, while water quality does not meet effluent standard quality for observed parameters including TSS, BOD, COD, oil & fat parameters and Total coliform. The LID concept that are suitable are Bio retention cell, Permeable Pavement and Rooftop disconnection.The use of this type of LID is significant enough to reduce runoff by 77% at outlet 1, 98% at outlet 2 and 73% at outlet 3 and decrease in some parameters of water quality by 77% to 100%.

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A multi-stakeholder framework for urban runoff quality management: Application of social choice and bargaining techniques

Cited by 65 publications

References 21 publications

Water Allocation Management Under Scarcity: A Bankruptcy Approach

Water Allocation Management Under Scarcity: A Bankruptcy Approach

Preference-Based Multi-Objective Optimization for Synchromodal Transport Using Adaptive Large Neighborhood Search

Low Impact Development (LID) as an effort to achieve a sustainable urban drainage system (SUDS). Case Study: Left Side Of Garang River Segment VI Semarang

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