A robust possibilistic programming model for water allocation problem

2019 ◽  
Vol 53 (1) ◽  
pp. 323-338 ◽  
Author(s):  
Mohamadreza Fazli-Khalaf ◽  
Karo Fathollahzadeh ◽  
Amir Mollaei ◽  
Bahman Naderi ◽  
Mohammad Mohammadi
Keyword(s):  
Real World ◽  
Water Allocation ◽  
Water Distribution ◽  
Programming Model ◽  
Fuzzy Model ◽  
Business Environment ◽  
Allocation Problem ◽  
Extended Model ◽  
Possibilistic Programming ◽  
Uncertainty Of Parameters

Over the past few years, water allocation problem has increasingly spotlighted by governments, researchers and practitioners. As water plays an important role in people’s life and business environment, the problem of water allocation should be considered carefully to properly satisfy demand of water consumers. In the real world applications, problems like water allocation are uncertain owing to long-term planning horizon of such problems. Therefore, employing efficient methods for tackling uncertainty of parameters should be regarded by field researchers. In this regard, this paper proposes a bi-objective mathematical programming model for water distribution network design. The extended model maximizes total profit of water distribution as well as maximizing priority of water transferring among water customer zones. Then, to cope effectively with uncertainty of parameters, a novel robust possibilistic programming method is applied. Then, fuzzy and robust fuzzy programming models are compared against each other and output results confirm superiority and effective performance of the robust fuzzy model in the water allocation problem. Also, output results of the extended model show its accurate performance that results in applicability of the model as a strong planning tool in real world cases.

A Multi-Period Multiple Objective Uncertain Programming Model to Allocate Order for Supplier Selection Problem

2016 ◽  
Vol 33 (06) ◽  
pp. 1650045
Author(s):  
Alireza Eydi ◽  
Leyla Fazli
Keyword(s):  
Real World ◽  
Supplier Selection ◽  
Deterministic Model ◽  
Programming Model ◽  
Business Environment ◽  
Sensitivity Analyses ◽  
Order Allocation ◽  
Basic Part ◽  
Allocation Process ◽  
Single Objective

As a basic part of organizations’ logistics management, purchasing function has supplier selection as one of its main responsibilities. One of the main objectives a buyer follows in supplier selection is to determine optimal quota to be allocated to each supplier. How to allocate orders to different suppliers is as important task as it may affect efficiency of the whole chain. Also, due to variations in real-world business environment, order allocation process is always associated with uncertainties that make it complicated. Therefore, a three-stage integrated framework with environmental uncertainties considered is proposed to allocate orders; this framework can determine qualified suppliers to whom it assigns optimal quota. Considering multi-period purchases and uncertainties, this framework presents a multi-objective nonlinear programming model to determine optimal quota to be allocated to each qualified supplier within each specified period. In order to have the order allocation process closer to real-world cases while increasing the reliability of the obtained solutions, time value of money, inflation, transportation modes, supplier’s profit, and pricing strategy are considered in this model. According to uncertain structure of the proposed model, a solution strategy is proposed to convert this model into a single-objective deterministic model. Then, the resulted single-objective deterministic model is solved by proposing three evolutionary metaheuristic algorithms based on cuckoo optimization algorithm and imperialist competitive algorithm. Finally, a sample problem is presented together with some statistical tests and sensitivity analyses to assess and examine the proposed framework.

scholarly journals Optimal Allocation of Surface Water Resources at the Provincial Level in the Uzbekistan Region of the Amudarya River Basin

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1446
Author(s):  
Min Wang ◽  
Xi Chen ◽  
Ayetiguli Sidike ◽  
Liangzhong Cao ◽  
Philippe DeMaeyer ◽  
...  
Keyword(s):  
River Basin ◽  
Water Allocation ◽  
Water Distribution ◽  
Optimal Allocation ◽  
Probability Distributions ◽  
Economic Benefits ◽  
Aral Sea ◽  
Incoming Flow ◽  
Provincial Level ◽  
Water Users

Water users in the Amudarya River Basin in Uzbekistan are suffering severe water use competition and uneven water allocation, which seriously threatens ecosystems, as shown, for example, in the well-known Aral Sea catastrophe. This study explores the optimized water allocation schemes in the study area at the provincial level under different incoming flow levels, based on the current water distribution quotas among riparian nations, which are usually ignored in related research. The optimization model of the inexact two-stage stochastic programming method is used, which is characterized by probability distributions and interval values. Results show that (1) water allocation is redistributed among five different sectors. Livestock, industrial, and municipality have the highest water allocation priority, and water competition mainly exists in the other two sectors of irrigation and ecology; (2) water allocation is redistributed among six different provinces, and allocated water only in Bukhara and Khorezm can satisfy the upper bound of water demand; (3) the ecological sector can receive a guaranteed water allocation of 8.237–12.354 km3; (4) under high incoming flow level, compared with the actual water distribution, the total allocated water of four sectors (except for ecology) is reduced by 3.706 km3 and total economic benefits are increased by USD 3.885B.

Water Scarcity and Conflict Between Upstream and Downstream Riparian Countries

2021 ◽  
Vol 07 (03) ◽  
pp. 2150012
Author(s):  
Sahar Farid Yousef
Keyword(s):  
Water Availability ◽  
Water Scarcity ◽  
Water Allocation ◽  
Allocation Problem ◽  
The Other ◽  
Backward Induction ◽  
Transboundary River ◽  
Militarized Conflicts ◽  
The Future ◽  
Water Scarce

More than one-quarter of the world’s population lives in water-scarce areas, while most countries share at least one transboundary river. If water scarcity is this prevalent, should we expect riparian countries to fight over the water allocation of shared rivers? To answer this question, I develop a modified one-shot three-stage river-sharing game where countries can resort to force to solve their water allocation problem. Using backward induction, I solve for the probability of the downstream country initiating conflict against the upstream country and the likelihood of the latter responding with force to the former’s hostile actions. I test the model empirically using a set of all upstream–downstream riparian dyads with available data from AQUASTAT and the Correlates of War Project for the years 1960–2010. The main contribution of this paper is that it demonstrates how upstream and downstream riparian countries differ in their decision to use force against the other country when experiencing water scarcity. I find that water scarcity increases the likelihood of the downstream country initiating the conflict, but it has no effect on the upstream country’s likelihood of responding with force. If history is a predictor of the future, then the results imply that as more riparian countries become water-scarce, militarized conflicts between upstream and downstream countries are likely to increase, especially if there is heterogeneity in water availability between the riparian dyad.

scholarly journals Optimization of Classification Track Assignment Considering Block Sequence at Train Marshaling Yard

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Yingqun Zhang ◽  
Rui Song ◽  
Shiwei He ◽  
Haodong Li ◽  
Xiaole Guo
Keyword(s):  
Integer Programming ◽  
Numerical Experiment ◽  
Real World ◽  
Programming Model ◽  
Block Sequence ◽  
Operational Process ◽  
Integer Programming Model ◽  
The Real ◽  
Reasonable Amount ◽  
Number Of Factors

An operational process at train marshaling yard is considered in this study. The inbound trains are decoupled and disassembled into individual railcars, which are then moved to a series of classification tracks, forming outbound trains after being assembled and coupled. We focus on the allocation plan of the classification tracks. Given are the disassembling and assembling sequence, the railcars connection plan, and a number of classification tracks. Output is the assignment of the railcars to the classification tracks. An integer programming model is proposed, aimed at reducing the number of coupling operations, as well as the number of dirty tracks which is related to the rehumping operation, and the order of the railcars on the outbound train must satisfy the block sequence. Tabu algorithm is designed to solve the problem, and the model is also tested by CPLEX in comparison. A numerical experiment based on a real-world case is analyzed, and the result can be reached within a reasonable amount of time. We also discussed a number of factors that may affect the track assignment and gave suggestions for the real-world case.

scholarly journals From Linear Programming Model to Mixed Integer Linear Programming Model for the Simultaneous Optimisation of Water Allocation and Reservoir Location in River Systems

Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 594 ◽  
Author(s):  
Jaime Veintimilla-Reyes ◽  
Annelies De Meyer ◽  
Dirk Cattrysse ◽  
Jos Van Orshoven
Keyword(s):  
Linear Programming ◽  
Network Flow ◽  
Water Allocation ◽  
Programming Model ◽  
Water Levels ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Network Configuration ◽  
Spatially Distributed ◽  
Lp Model

The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a Network Flow Optimisation (NFO) problem and addressed by Linear Programming (LP). In this paper we present an extension of the strategic NFO-LP model to simultaneously optimise the allocation of water and the location of one or more reservoirs. The applicability of the MILP model has been illustrated by applying it to a hypothetical river network configuration consisting of seven candidate reservoir nodes and seven demand nodes, and by comparing the outcome (water levels in selected reservoir, penalties) with the values obtained by the original LP-model for the same network with six reservoirs present.

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