writing a literature Critique

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The literature critique is a brief summary of an article from a 'refereed' journal (SEE THE ARTICLE IN THE ATTACHMENT). Critiques must be word-processed, single spaces and at most one page. Also, you must have a minimum margin size of 1 inch and maximum margin size of 1 inch on all sides (i.e., where the top, left and right sides are even) of your submitted assignment. Occasionally, your article may not fully reach the bottom margin due to the writing of your summary; thus, if this occurs, you must not leave more than a 1.5" margin at the bottom in any case.

The only accepted font size must be 12 pt and Times New Roman font type is required. The paper should contain 4-5 well-written paragraphs with proper grammar and spelling. In the final paragraph, briefly discuss something from the article that really impressed you. Only the last paragrage can be written from the first person point of view, but not in any other location of the literature critique should 1st or 3rd person be used (i.e, do not use 'we', 'you', 'I', etc.). The reference must be in APA-Style

At the top of the assignment, please include the following:

Literature Critique #2

Date Due: December 13, 2019

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From the SelectedWorks of Ahmad ShahiriParsa 2015 Introduction to Linear Programming as a Popular Tool in Optimal Reservoir Operation, a Review Ahmad ShahiriParsa Mohammad Noori Mohammad Heydari, Dr Faridah Othman Kourosh Qaderi Available at: https://works.bepress.com/ahmad-shahiriparsa/5/ Advances in Environmental Biology, 9(3) February 2015, Pages: 906-917 AENSI Journals Advances in Environmental Biology ISSN-1995-0756 EISSN-1998-1066 Journal home page: http://www.aensiweb.com/AEB/ Introduction to Linear Programming as a Popular Tool in Optimal Reservoir Operation, a Review 1Mohammad Heydari, 2Faridah Othman, 3Kourosh Qaderi, 4Mohammad Noori and 5Ahmad ShahiriParsa 1 PhD candidate, Faculty of engineering, University of Malaya, Kuala Lumpur Associated professor, Department of civil Engineering, Faculty of Engineering, Kuala Lumpur, Malaysia Assistant Professor, Department of Water Engineering, Shahid Bahonar University of Kerman, Iran 4 PhD candidate, Faculty of Engineering, Ferdowsi University, Mashhad, Iran 5 Graduated student, Faculty of Engineering, University of UNITEN, Kuala Lumpur, Malaysia 2 3 ARTICLE INFO Article history: Received 21 November 2014 Received in revised form 4 December 2014 Accepted 3 January 2015 Available online 28 January 2015 Keywords: Linear programming, LP, optimal operation, multiple reservoirs, optimization, mathematical modeling. ABSTRACT Water is a rare and vital natural resource for all biological phenomena and human activities that continuously is needed to be known at any time and place. Taking into the burgeoning growth of population and consequently increasing human needs, the limitation of water resources is a considerable challenge for human. Moreover, asymmetrical distribution of rain time and location in most countries has caused that the water resources management and programming be considered. In order to resolve this problem, researchers are trying to use some techniques in relation with programming and management for a long time. Most of practical and applied problems can be modeled as a linear programming problem regarding all intrinsic complexities. The mentioned reason and also presence of different solving software of linear programming problems have caused that linear programming be used as one of the most practical methods in the field of dam operation for years. In this research, we introduce optimal operation problems of reservoirs by using linear programming techniques and discuss about them. Also, objective and multi objective models were introduced by using some questions. Finally, some popular methods in the field of modeling such problems are introduced. © 2015 AENSI Publisher All rights reserved. To Cite This Article: Mohammad Heydari, Faridah Othman, Kourosh Qaderi, Mohammad Noori, Ahmad ShahiriParsa. Introduction to linear programming as a popular tool in optimal reservoir operation, a Review. Adv. Environ. Biol., 9(3), 906-917, 2015 INTRODUCTION Water is the most important requires for all living creatures after oxygen. Life and health of all beings containing human, plants and animals, depends on water. Therefore, nowadays, water is known as human treasure. Although 75 percent of planet earth is composed of water, but only one percent of the fresh water is usable. In spite of the fact that the amount of usable water (drinking water) on earth is limited, but this insignificant amount is not spread on the earth uniformly. This limitation is one of the most important and essential challenges in countries with arid and semi-arid regions. On one hand, limited access to water resources and on the other hand, human need for water, necessitate the proper management strategies. Taking into aims like providing water, controlling floods, hydro power production, tourism, etc. dams are designed and constructed in order to resolve such problems. Providing water for municipal, agricultural and industrial consumption is one of the main purposes for reservoir operation and planning. In most countries, agricultural purposes has the highest water level consumption. So, optimal operation and management of water resources, among giving proper response to the needs of this part, leads to reduced waste water and increasing the level of yield of production and gaining sustaining development in agriculture [1]. Flood control and decreasing its resulted damage are another aims of constructing dams. Besides dams as main sources in providing water, these also have high capacity in the field of growing and developing tourism industry. In most countries in the world, dams and their reservoirs are counted as the most important tourist absorption and absorb numerous tourists annually. One of the aims of constructing dams is hydroelectric Corresponding Author: Faridah Othman, Associated professor, Department of civil Engineering, Faculty of Engineering, Kuala Lumpur, Malaysia. Ph: 0379674584; E-mail: Faridahothman@um.edu.my 907 Mohammad Heydari et al, 2015 Advances in Environmental Biology, 9(3) February 2015, Pages: 906-917 energy. Nowadays, the hydropower and thermal energies have the highest share in producing the world`s electricity. Although, problems and limitations of producing electricity in thermal power sources and due to technical issues, the imperatives of environmental criteria, resources constrains have caused that, by the time the general trend in the world of power generation, hydroelectric plants will be more attentive. The potential energy of water behind a dam, provide hydroelectric energy. In this case the energy of the water depends on stored water of dam and height difference between the water source and the withdrawal of water from the dam. Power generation in hydroelectric plants has a lot of advantages. Perhaps these benefits have caused that this production method has comparative advantages and are considered in the world, especially in countries where water resources are relatively substantial. By constructing the dam in areas of water in the river and the regions where rainfall is high and installing turbine, the gravitational potential energy of water behind the dam can be used to generate hydroelectric power. The next issue is the optimal operation of the reservoir, considering the objectives like drinking water needs, industrial, agricultural, hydroelectric purposes, flood control, tourism and etc. For this purpose, efficient approaches and appropriate solutions must be considered for operating reservoirs as one of the most important components of water resources. Application of such approaches leads to create balance between available limited resources and high consumption, optimization of water use in agriculture, municipal and industry and finally sustainable development in water resources management. Nowadays, the water management and water protection are high importance in developing and developed countries. In order to system enhancement and equitable management of water resources, using the principles and technical planning is necessary. Using planning technique practical and practicable in order to optimize water resources, due to its simplicity and applicability has special status. Charles Revelle in 1969 decided to act for design and reservoir management by linear programming and using a Linear Decision Rule (LDR). In this linear decision making method, reservoir outflow in whole operation period calculated as the difference between the storage of the reservoir at the beginning of the period and decision parameter by solving linear programming [2]. In 1970, Loucks applied the linear model with its probable limitation and its deterministic equivalent for solving the system of reservoirs. Cai and his collaborators in 2001, used genetic algorithm with linear programming in complex problems of water reservoir. The gained results have been reported very satisfactory [3]. in 2005, Reis et al. used combination of Genetic Algorithm (GA) and Linear Programming (LP) method designed and solved planning and decision-making for reservoirs of water systems during the probabilistic [4]. in 2006, Reise and his associates in performed a combination method using genetic algorithm (GA) and linear programming (LP) in order to achieve operational decisions for a system reservoir that is applied during optimization term. This method identifies a part of decision variables named Cost Reducing Factors (CRFs) by Genetic Algorithm (GA) and operational variables by Linear Programming (LP) [5]. Optimization Process: The optimization process of this study is presented in Figure 1, and it consists of seven vital steps. 1) A detailed view 2) Problem definition 3) Developing mathematical model 4) Finding solution for the model 5) Sensitive analysis phase 6) Validation 7) Performing the solution Fig. 1: Schematic representation of optimization process. 908 Mohammad Heydari et al, 2015 Advances in Environmental Biology, 9(3) February 2015, Pages: 906-917 1. The first step in this process is expanding a clear understanding of the problem with a detailed view of the real world. To this end, a number of primitive solutions to achieve objectives must be defined that consider different aspects of the problem. Also, some doubts should be in the minds of decision makers as to which opinion to achieve the goal is best. 2. Problem definition phase is a phase in which a precise and clear statement of the problem taken from observations must be made and be gained in identification phase and transparency step of the problem. The mentioned problem definition should define purpose, the influence of the initial solutions, assumptions, barriers, limitations and possible available information on sources and markers involved in the problem. Experience shows that erroneous definition of the problem leads to analysis failure. 3. When we define the problem, the next step is developing a mathematical model. The mathematical model is mathematical performance of the system or real problem and is able to perform different aspects of the problem in interpretable form. At first it may be that qualitative model structure itself, including unofficial descriptive approach. In this unofficial qualitative model, an official model may develop. (Part 3 contains some applied models in order to optimize reservoir operations of dams.) 4. After formulating and developing the model, it is turn to find a solution for the model. Usually the optimal solution for the model with evaluation outcome sequence is found. This sequence of operation starts from a primitive solution that is as input of the model and the generation of the developed solution as output that is known as repeat is resulted. The developed output is resubmitted as a new input and the process is repeated under the certain circumstances. 5. Another important phase of this study is sensitive analysis phase. Performing the sensitivity analysis allows us to determine the necessary accuracy on input data and understanding the decision variables that have the highest influence on the solution. The sensitivity analysis allows the analyst to see how sensitive the preferred option of changing assumptions and data is. By performing the sensitivity analysis, we will be able to recognize how strong is a preferred opinion and input data what need to change to become an optimal choice. In sensitivity analysis, analyst modifies the suppositions or data to enhance the considered option and convert it into optimal choice. Amount of default modification is measuring is determining the power of the model. 6. A solution should be tested. Often the solution is tested in a short or long term. The proposed solution must be validated against the actual performance observation while the test is being made, and also it should be independent of how an optimal solution is obtained. 7. The final phase is performing the solution. This is the step of using optimal outputs for decision making process. Usually, analyst converts his mathematical findings as a series of understandable and applicable decisions. It may be necessary to train decision-makers to help them apply the findings to attain the required changes from the current situation to the desired situation. Also, they need to be supported until they learn the mechanism of maintenance and upgrading the solution. Fig. 2: Allocating the capacity of reservoir to different volumes (adopted from [6]). 909 Mohammad Heydari et al, 2015 Advances in Environmental Biology, 9(3) February 2015, Pages: 906-917 Reservoirs Operation Modelling: The main objective of optimization is finding the best acceptable solution. There may be different solutions for a problem that in order to compare them and choose the optimal solution, the objective function is defined. The choice of this function depends on the nature of the problem. An Optimization problem with one objective is called (single objective problems), and When several objectives and criteria are considered for minimizing or maximizing the optimization problem, then it is called (multi-objective optimization problems). Some conditions of optimization model structures for the operation of the reservoir are given in below. Single objective models: Objective function by minimizing the total flood damage in its simplest form is defined as a function of flow rate in vulnerable areas as follows: Min Z = (t Є T) (1) Subject to: f(It,Rt) = 0 (2) Rt ≥ Rmin (3) Rt ≤ Rmax (4) St+1 = St + It - Rt (5) Smin ≤ St+1 ≤ Smax (6) │Rt+1 - Rt│≤ ЄR (7) Where: Z: value of objective function Qt: flow rate at damage point t: time index T: time horizon of operation It: flow rate Rt: reservoir outflow that their relationship is expressed by the function as a power constraint. St: reservoir storage Rmin and Rmax: minimum and maximum release values. ЄR: limiting the maximum difference between release values at two successive time steps It: inflow to the reservoir In other models as seen in the relations 8 to 11, the released volume in studied periods is considered as a function of the river basin or reservoir storage. Among these, the function that estimated best value of the objective function is selected as optimal function. This function performs some constant factors for any period during the statistical term. According to it, the release amount can take a percentage of the river basin, save volume or a combination of both. The following is with agricultural purpose and for a reservoir: Min Def = 2 (8) Subject to: St+1 =St - Qt - Rt – Lt (St, St+1)- Spt (9) Smin ≤ St ≤ Smax (10) Rmin ≤ Rt ≤ Rmax (11) Where: Def: the monthly shortage Rt: released volume of reservoir Dt: amount of the required monthly Dmax: maximum required during a statistical period St: storage volume at the beginning of month Qt: inflow to river during the period t Lt (St, St+1) is calculations of evaporation losses in period t that creates a set of implicit nonlinear equations. Spt: is overflow from the reservoir during the period. Smax and Smin are in order the maximum and minimum volume of reservoir storage, in order to providing the dead storage of the reservoir and renewable and purposes of flood control volume. Rmin and Rmax are in order the minimum and maximum outflow from the reservoir. If a single-objective optimization problem has multiple optimal solutions, it does not matter which one is selected, as they give the same objective function value. 910 Mohammad Heydari et al, 2015 Advances in Environmental Biology, 9(3) February 2015, Pages: 906-917 Yield Model: Discharge model is a linear optimization model. Discharge refers to the flow of future periods with relatively high credit (or with probability equal to or exceeds above) can be supplied. In this model, the relationship between the two series is creating volumetric balance in storage volume during the year. Inter year relations: Sy+ Qy – YFIRM – α P,Y Yp– Ey – Ry = S y+1 αP,Y= Sy≤ka0 Ey= E0 + [ Sr +∑ ( St + St+1 / 2 ) ᵞ1].E In these formulas the various parameters are as follows: Sy: The storage at the beginning of the period Qy: Annual input YFIRM: Annual primary requires Yp: Annual secondary require Ey: Evaporation Ry: Additional output ka0: Storage volume of out year St: Storage volume at the start of the period E: Amount of annual evaporation E0: The fixed amount of annual evaporation ᵞ1: The relative rate of evaporation of the month (12) (13) (14) (15) Extra year relations: St + Qt– YFIRM,t –Ypt – et –Rt = St+1 (16) KD + ka0+ St+Kft≤ K (17) et= ᵞt .E0+ ( St + St+1 ) ᵞt .Et (18) In this relation we have: Qt: Average of monthly period et : Monthly evaporation KD: Dead storage Kft: Flooding control volume Because the critical condition determines the reservoir volume, sometimes the relation 15 can be written as follows. St + βt –et – rt =St+1 (19) In this case the model is called the approximate discharge model: βt: The relative coefficient of flow in the driest month of the year To fit the size of the reservoir, this model depends on value and river discharge. In some projects, due to the large fluctuations in discharge and a mismatch between the needs, the model requires reservoir storage volume greater than the existing one. Advantage of discharge model is in performing the results and the simplicity of application in simulation. Moreover, the simulation results clearly show the deficit and reduce the severity of the shortage. Multi-objective: Multi-objective optimization problems (MOPs) are common. They can be either defined explicitly as separate optimization criteria or formulated as constraints. Formally, this can be defined as follows. Definition of Multi-objective Optimization Problem: A general MOP includes a set of n parameters (decision variables), a set of k objective functions, and a set of m constraints. Objective functions and constraints are functions of the decision variables. The optimization goal is to: Maximize y= f (x) = (f1 (x), f2 (x)… fk (x)) (20) Subject to: e(x) = (e1(x),e2(x),…, em(x)) ≤ 0 (21) Where x = (x1, x2… xn) X (22) y =(y1, y2… yn) Y (23) And x is the decision vector, y is the objective vector, X is denoted as the decision space, and Y is called the objective space. The constraints e (x) ≤ 0 determine the set of feasible solutions. 911 Mohammad Heydari et al, 2015 Advances in Environmental Biology, 9(3) February 2015, Pages: 906-917 Feasible Set: The feasible set X f is defined as the set of decision vectors x that satisfy the constraints e.x: Xf = {x X | e (x) ≤ 0} (24) The image of Xf , i.e., the feasible region in the objective space, is denoted as Yf = f (Xf) = Ux Xf {f(x)}. (25) Without loss of generality, a maximization problem is assumed here. For minimization or mixed maximization/minimization problems the definitions presented in this section are similar. In single-objective optimization, the feasible set is completely (totally) ordered according to the objective function f(x). The structure of a basic model that is the base of many optimization modes of reservoirs’ operation is as follows: Minimize Z= (26) Subject to: St+1=St+it-Rt-Et-Lt (t=1,2,3,…n) (27) Smin≤St≤cap (t=1,2,3,…n) (28) 0≤Rt≤Rmax,t (t=1,2,3,…n) (29) St.Et.Lt.Rt≥0 (t=1,2,3,…n) (30) In which, the variables are defined as follows: Z: objective function Loss: operation cost in month t that is function of output and required storage and volume of the reservoir in month t. Rt: released volume of reservoir Dt: amount of monthly need St: volume of storage reservoir in month t n: length of planning period Smax and Smin are in order the maximum and minimum storage of water in reservoir. Rmax is the maximum outflow from the reservoir during period t. Cap: total volume of water stored in the reservoir. Et: amount of evaporation of the reservoir in month t. Lt: volume of water leaks in the reservoir in month t. It: volume of inflow...
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Water is a very crucial thing in the whole world. Without water, all the continents would be
formless, as every living creature and the non-living creature that depends on water for survival
would die. Although bout 75 percent of the planet is covered by water, its limitation remains a
big challenge. The main reason for this is that it is not evenly distributed within all parts of the
world. Some parts are having a lot of water while some parts are rid and semi-arid. Some part
has a lot of water; unfortunately, this water is not usable by both human and animal hence
rendering this place to be water deficit when considering it...

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Cornell University

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