Linear goal programming approach to obtaining the weights of intuitionistic fuzzy ordered weighted averaging operator

The multiple attribute decision making problems are studied, in which the information about attribute weights is partly known and the attribute values take the form of intuitionistic fuzzy numbers. The operational laws of intuitionistic fuzzy numbers are introduced, and the score function and accuracy function are presented to compare the intuitionistic fuzzy numbers. The intuitionistic fuzzy ordered weighted averaging （IFOWA） operator which is an extension of the well-known ordered weighted averaging （OWA） operator is investigated to aggregate the intuitionistic fuzzy information. In order to determine the weights of intuitionistic fuzzy ordered weighted averaging operator, a linear goal programming procedure is proposed for learning the weights from data. Finally, an example is illustrated to verify the effectiveness and practicability of the developed method.

Goal programming approach for sustainable forest management(case study in Iranian Caspian forests)

We used a goal programming technique to determine the optimal harvest volume for the Iranian Caspian forest. We collected data including volume, growth, wood price at forest roadside, and variable harvesting costs. The allometric method was used to quantify seques- trated carbon. Regression analysis was used to derive growth models. Expected mean price was estimated using wood price and variable harvesting costs. Questionnaire was used to determine the constraints and the equation coefficients of the goal programming model. The optimal volume was determined using the goal programming method according to multipurpose forest management. LINGO software was used for analysis. Results indicated that the optimum volumes of species were 250.25 m3.ha-1 for beech, 59 m3.ha-1 for hornbeam, 73 m3.ha-1 for oak, 41 m3.ha-1 for alder, and 32 m3.ha-1 for other species. The total optimum volume is 455.25 m3.ha-1.

HEURISTIC MODELING FOR A DYNAMIC AND GOAL PROGRAMMING IN PRODUCTION PLANNING OF CONTINUOUS MANUFACTURING SYSTEMS

At the first sight it seems that advanced operation research is not used enough in continuous production systems as comparison with mass production, batch production and job shop systems, but really in a comprehensive evaluation the advanced operation research techniques can be used in continuous production systems in developing countries very widely, because of initial inadequate plant layout, stage by stage development of production lines, the purchase of second hand machineries from various countries, plurality of customers. A case of production system planning is proposed for a chemical company in which the above mentioned conditions are almost presented. The goals and constraints in this issue are as follows： （1） Minimizing deviation of customer＇s requirements. （2） Maximizing the profit. （3） Minimizing the frequencies of changes in formula production. （4） Minimizing the inventory of final products. （5） Balancing the production sections with regard to rate in production. （6） Limitation in inventory of raw material. The present situation is in such a way that various techniques such as goal programming, linear programming and dynamic programming can be used. But dynamic production programming issues are divided into two categories, at first one with limitation in production capacity and another with unlimited production capacity. For the first category, a systematic and acceptable solution has not been presented yet. Therefore an innovative method is used to convert the dynamic situation to a zero- one model. At last this issue is changed to a goal programming model with non-linear limitations with the use of GRG algorithm and that＇s how it is solved.

Optimizing the Asset and Liability Management of Telecommunication Company using Goal Programming Model

Since the telecommunications companies experience great competition,high churn rate,data traffic issues during the Covid-19 pandemic and the upgrade to 5G connectivity,the finance management of a telecommunications company should be analyzed to study the volatility and returns in the sector.This paper aims to develop a goal programming model to examine the asset and liability management of a telecommunication company,namely Telekom Malaysia Berhad(TM)in Malaysia.The result of this study shows that TM has achieved all the goals in maximizing assets,equities,profits,earnings and optimum management item while minimizing liabilities over the period of study from 2015 to 2019.Potential improvements on these goals have also been identified through this study.This paper has also contributed to the studies in financial management since past studies have not been done on asset and liability management in telecommunications companies which is rapidly growing and expanding even while the world is suffering from economy crisis during this pandemic.

Modeling of Catfish Farm Using Lexicographic Linear Goal Programming

In this paper, a fish farm was modeled using the Lexicographic linear goal programming approach due to incommensurability in objectives. The study considered the fish farming plan with two sizes of catfish from stocking to harvesting at four-month intervals. The multi-objective goals developed are required raw materials feed, water, light (resource utilization), sales revenue, profit realized, labor utilization, production costs, and pond utilization. The developed model was tested using related data collected from the farm records with the use of TORA 2007 software. The compromised solution from the results showed that the developed model is an efficient tool for decision-making process in the fish farm business organization.

A Note on Standard Goal Programming with Fuzzy Hierarchies: A Sequential Approach

In the paper [Standard goal programming with fuzzy hierarchies: a sequential approach, Soft Computing, First online: 22 March 2015], it has been assumed that the normalized deviations should lie between zero and one. In some cases, this assumption may not be valid. Therefore, additional constraints must be incorporated into the model to ensure that the normalized deviations should not exceed one. This modification is illustrated by the given numerical example.

Goal Programming for Stable Mode Transition in Tandem Turbo-ramjet Engines

This article, in order to guarantee the stable mode transition in tandem turbo-ramjet engines, investigates the multi-objective and multi-variable goal programming algorithm. First, it introduces the structural features of the variable cycle turbo-ramjet engines, the principles of selecting the mode transition operation point and the design parameters, and the characteristics of the turbofan mode and the ramjet mode. Second, a component-based variable cycle turbo-ramjet engine model is developed to simulate the mode transition process. Third, the Newton-Raphson algorithm is used to solve the multi-variable and multi-objective optimization problem. The results show that with the maximum residua of only 0.06%, this algorithm has an acceptable convergence that meets the predetermined goals. Finally, the simulation shows that the stable turbo-ramjet mode transition could be realized with the mode transition control law developed by the algorithm.

Generalized Goal Programming and Its Application in Water Environmental System

This paper presents the concept of generalized goal programming (GGP), the characteristics of the programming model is "designing optimum system". Firstly, based on the synthesis of goal programming and Denovo programming, one type of generalized goal programming model is established. In the paper the properties of feasible region is studied. Secondly, GGP is enlarged to the case that fuzzy parameters and fuzzy goal sets exist in the GGP model, the solution methods using fuzzy set theory for GGP with fuzzy parameters are provided. Finally, this approach has been used to analyse a water environmental system in coastal city, thus proving its usefulness.

Mergers and Acquisitions: An Efficiency Evaluation

This article sheds light on how synergies arise through mergers and acquisitions (M&A). Enterprises go through the process of Mergers and Acquisitions (M&A) with the goal of improving performance, increasing efficiency and obtaining business synergy. Prior literature suggests that synergies could arise due to taxes, market power or efficiency improvements. This study evaluates the efficiency of M&A in Brazil among publicly-traded companies. We used models with multiple objectives from Goal Programming and Data Envelopment Analysis (GPDEA), employing accounting indicators as input and output variables, and thus evaluated the emergence of synergy gains. These models allow us to analyze and classify the M&A according to the efficiency obtained in such processes. Some of the M&A cases analyzed were mistakenly considered efficient when used traditional models. And, as expected, the GPDEA was proved to be superior to classical models;however it was noticed that few of the cases investigated were proved to be effective. We presented a new application for multi-objective approach that can be used to assess mergers and acquisitions. The dualapplication of GPDEA provided a greater understanding of efficiency generation in synergy creation by means of M&A.

THE ROLLING DEVELOPMENT MODEL OF ECOLOGICAL ECONOMY COMBINED WATER CONSERVANCY CONSTRUCTION WITH SCHISTOSOMIASIS CONTROL

On the basis of classification of geographical properties a rolling develop-ment goal programming model is formulated in correspondence with the ecopatterngroup in Four-Lake Area. In this model, the control of schistosomiasis and strengthen-ing of the drainage-storage function are both regarded as ecological measures duringthe process of multi-year(r_0) ecological economic rolling development to make theecoagricultural system in this area ioto a stably operating, ordered, and good cyclicsystem under the support of some controllable factors.

Relating Optimization Problems to Systems of Inequalities and Equalities

In quantitative decision analysis, an analyst applies mathematical models to make decisions. Frequently these models involve an optimization problem to determine the values of the decision variables, a system S of possibly non- linear inequalities and equalities to restrict these variables, or both. In this note, we relate a general nonlinear programming problem to such a system S in such a way as to provide a solution of either by solving the other—with certain limitations. We first start with S and generalize phase 1 of the two-phase simplex method to either solve S or establish that a solution does not exist. A conclusion is reached by trying to solve S by minimizing a sum of artificial variables subject to the system S as constraints. Using examples, we illustrate how this approach can give the core of a cooperative game and an equilibrium for a noncooperative game, as well as solve both linear and nonlinear goal programming problems. Similarly, we start with a general nonlinear programming problem and present an algorithm to solve it as a series of systems S by generalizing the “sliding objective function method” for two-dimensional linear programming. An example is presented to illustrate the geometrical nature of this approach.

Sequential Ordering Algorithm for Mass Integration: The Case of Direct Recycling

In the last three decades much effort has been devoted in process integration as a way to improve economic and environmental performance of chemical processes. Although the established frameworks have undergone constant refinement toward formulating and solving complicated process integration problems, less attention has been drawn to the problem of sequential applications of mass integration. This work addresses this problem by proposing an algorithm for optimal ordering of the process sinks in direct recycling problems, which is compatible with the typical mass integration formulation. The order consists in selecting the optimal sink at a specific integration step given the selection of the previous steps and the remaining process sources. Such order is identified through a succession of preemptive goal programming problems, namely of optimization problems characterized by more objectives at different priority levels. Indeed, the target for each sink is obtained by maximizing the total flow recycled from the available process sources to this sink and then minimizing the use of pure sources, starting from the purest one;the hierarchy is respected through a succession of linear optimization problems with a single objective function. While the conditional optimality of the algorithm holds always, a thorough statistical analysis including structured to random scenarios of process sources and process sinks shows how frequently the sequential ordering algorithm is outperformed with respect to the total recycled amount by a different selection of process sinks with the same cardinality. Two more case studies proving the usefulness of ordering the process sinks are illustrated. Extensions of the algorithm are also identified to cover more aspects of the process integration framework.

A Decision Model for Selecting Participants in Supply Chain

In order to satisfy the rapid changing requirements of customers, enterprises must cooperate with each other to form supply chain. The first and the most important stage in the forming of supply chain is the selection of participants. The article proposes a two staged decision model to select partners. The first stage is the inter company comparison in each business process to select high efficiency candidate based on inside variables. The next stage is to analyse the combination of different candidates in order to select the most perfect partners according to a goal programming model.

Research Priorities and Drilling Goals of Ocean Drilling Program

The research priorities and drilling goals of Ocean Drilling Program are introduced from two scientific themes. The scientific theme of dynamics of earth’s environment try to understand earth’s changing climate, causes and effects of sea—level change, and other problems such as global carbon cycle, formation of gas hydrates and submarine

Harvest optimization for sustainable agriculture:The case of tea harvest scheduling

To ensure sustainability in agriculture,many optimization problems need to be solved.An important one of them is harvest scheduling problem.In this study,the harvest scheduling problem for the tea is discussed.The tea harvest problem includes the creating a harvest schedule by considering the farmers'quotas under the purchase location and factory capacity.Tea harvesting is carried out in cooperation with the farmer-factory.Factory man-agement is interested in using its resources.So,the factory capacity,purchase location capacities and number of expeditions should be considered during the harvesting process.When the farmer's side is examined,it is seen that the real professions of farmers are different.On harvest days,farmers often cannot attend to their primary professions.Considering the harvest day preferences of farmers in creating the harvest schedule are of great importance for sustainability in agriculture.Two different mathematical models are proposed to solve this problem.The first model minimizes the number of weekly expeditions of factory vehicles within the factor and purchase location capacity restrictions.The second model minimizes the number of expeditions and aims to comply with the preferences of the farmers as much as possible.A sample application was performed in a region with 12 purchase locations,988 farmers,and 3392 decares of tea fields.The results show that the compli-ance rate of farmers to harvesting preferences could be increased from 52%to 97%,and this situation did not affect the number of expeditions of the factory.This result shows that considering the farmers'preferences on the harvest day will have no negative impact on the factory.On the contrary,it was concluded that this situation increases sustainability and encouragement in agriculture.Furthermore,the results show that models are effective for solving the problem.

Multi-Objective Vendor Selection Problem of Supply Chain Management Under Fuzzy Environment

Survival of a company in today's competitive business environment depends mainly on its supply chain.An adequate supply chain gives a competitive edge to a com-pany.Sourcing,which is the initial stage of a supply chain,can be made efficient by making an appropriate selection of vendors.Appropriate vendor selection results not only in reduced purchasing costs,decreased production lead time,increased customer satisfaction but also in improved corporate competitiveness.In general,the vendor selection problem is a multi-objective decision-making problem that involves some quantitative and qualitative factors.So,we have considered a multi-objective ven-dor selection problem(MOV SP)with three multiple objective goals:minimization of net ordering price,minimization of rejected units and minimization of late delivered units.In most of the cases,information about the price of a unit,percentage of rejected units,percentage of late delivered units,vendor rating value and vendor quota flexibil-ity may not be known precisely due to some reasons.In this paper,imprecision in input information is handled by the concept of a simulation technique,where the parameter follows the uniform distribution.Deterministic,stochastic,a-cut and ranking function approaches are used to get the crisp value of the simulated data sets.The four differ-ent algorithms,namely-fuzzy programming,goal programming,lexicographic goal programming and D1-distance algorithm,have been used for solving the MOVSP.In last,three different types of simulated data sets have been used to illustrate the work.

Application of Integrated Multiple Criteria Data Envelopment Analysis to Humanitarian Logistics Network Design

This paper considers a humanitarian logistics network(HTLN)design problem,including the emergency relief facilities(ERFs)location-allocation decision for the efficient distribution of emergency supplies from the ERFs to the affected areas.A goal programming(GP)approach is applied to consider the multiple objectives simultaneously.Solving the GP model with a given weight assigned to each goal yields a single HTLN scheme,so there will be various schemes available by solving the GP with multiple values of the weights.For evaluating these schemes and identifying the most efficient one,we apply the data envelopment analysis(DEA)methods considering each scheme as a decision-making unit(DMU).Since the classical DEA(C-DEA)intrinsically aims to identify efficient DMUs and the efficient frontier,the use of C-DEA may not lead to a full ranking in many situations.There are several independent evaluation approaches to increasing discriminating power.Among them,this study integrates the multiple criteria DEA(MC-DEA)with the following three DEA methods,(i)stratification DEA(S^DEA),(ii)cross-efficiency DEA(CE-DEA),and(iii)super-efficiency DEA(SE-DEA),to make the most use of each method's strengths.Through a case study of designing the HTLN system for South Carolina,the procedure of implementing the integrated multiple criteria DEA(IMC-DEA)method is demonstrated.It is observed that the IMCDEA method performs well in terms of designing the HTLN system and would help the decision-makers consider more efficient options and make a final decision.

A Class of Genetic Algorithms on Bilevel Multi-objective Decision Making Problem

In this paper, it is discussed that the method on how to transform the bilevel multi objective decision making problem (BMDMP) into the equivalent generalized multi objective decision making problem. In order to better embody the decision maker′s hope and desire, we can transform it into the goal programming problem by means of genetic algorithms and obtain the goal optimization solution. The method which is satisfactory is elaborated in the following example.

Determining an optimum pattern of mixed planting from organic and non-organic crops with regard to economic and environmental indicators:A case study of cucumber in Kerman,Iran

Today,planning procedures which are used in different fields of decision making such as determination of optimum planting patterns are considered as important management issues.The importance of optimum planting patterns is highlighted when we learn that agricultural measures may have environmental side effects.Most economical analyses only focus on increasing economic gains of the farmers without regard to its environmental consequences.Therefore,one can argue that efficient managers should consider multiple purposes that cover both economic and environmental goals at the same time.This study attempted to identify an optimum mixed model of organic and non-organic production systems using a combination of AHP(Analytical Hierarchy Process)approach andWeighted Goal Programming to consider environmental and economic indicators simultaneously.This procedure was employed in the current design to determine and compare an optimum pattern of mixed planting of organic and non-organic products.The study sample was cucumber,investigated in four farming systems:organic open field farming system,nonorganic greenhouse farming system,non-organic tunnel farming system and open field non-organic farming system in Jiroft,Kerman,with regard to paper indices.Following the proposed MCDM(Multiple Criteria Decision Making)model,cucumber planting in open field non-organic farming system was replaced by open field organic farming system.Economic and environmental indicators rose by 11.97%and 21.40%respectively in MCDM proposed plan in comparison with the existing farm plan,which indicates the feasibility of MCDM proposed plan in terms of economic and environmental indicators.

A Multi-Criteria Optimization Method for Electrical Distribution System and Its Analysing in Practice

In this paper, the author explains the problem that we have to consider multiple goals and multiple factors which are usually affected by others at the same time in practical work for electrical power distribution system programming. A new mathematics model is set up here for the multiple goals programming of electrical power distribution system which includes various load control alternatives. An arithmetic and current software for the multi-criteria optimization of electrical power distribution system are given here. The author calculates and analyses the optimal programming projects and the optimal operation strategies for a practical system, which show that the model, the arithmetic and the current software are all correct and effective. The outcome of researches has been adopted by the authoritative persons.