Multiple Goal Programming Research Articles

Strategy for Managing the Potential for the Development of Environmentally Friendly Superior Grapes Products in the Probolinggo City

Community economic empowerment is a crucial part of the purpose of decentralization initiatives, which is to create an autonomous territory. Local governments and their communities manage their current resources and set up patterns of partnerships with the private sector in order to generate new jobs and increase the growth of economic activity in the area. The goal of this study was to build a policy model for the management of superior commodities of grapes in Probolinggo City as well as to assess the potential of the superior commodity of grapes and the viability of realizing that potential. In Probolinggo City, grapes have the potential to be a fundamental commodity. To get the feasibility value, the extended analysis method is applied. Utilizing the multiple goal programming paradigm, it is possible to assess the advantages of effectively controlling grape production. Due to the jobs and money it generates, grape farming meets these two criteria, making it both economically and socially viable. This makes it possible for grape farming to function at its best capacity and deliver the finest outcomes. According to the results of the SWOT analysis, aggressive planning was required to achieve the best management of the growth of the grape farming business. In grape growing, producers or the community can enhance productivity outcomes by engaging in the right cultivation management activities. They must, however, limit the holding area used to that of the ideal area.

Preface: Recent advances in multiple objective optimization and goal programming

Preface: Recent advances in multiple objective optimization and goal programming

Energy sources analysis and optimization of energy efficiency and greenhouse gases in production of farm crops

ABSTRACT The present current study aimed at analyzing the input–output energies and optimizing energy efficiency and greenhouse gases (GHG) in crops production at the northeast of Iran. The results of this research showed that the total energy inputs were equal to 42.4, 28.6, and 72.8 GJha−1 for, wheat, barley, and sugar beet, respectively. It was also shown that the highest energy efficiency, the lowest GHG emissions, and GHG intensity all belonged to barley production. The highest percentage of GHG intensity pertained to sugar beet production (41%), which was followed by wheat (38%) and barley (21%). It was also revealed that GHG intensity is a better criterion for the study of GHG since it also makes use of the energy output information in crops. The optimal model responses for the crop type and proper cultivation planning was 284432 hectares in terms of barley production, while those responses for wheat and sugar beet were zero and, thereby, they were eliminated from the model of Multiple Goal Programming (MGP). In the same way, this model could increase energy efficiency to 444875, while GHG emissions and its intensity decreased by 213259 tonCO2eq and 1.3 tonCO2eq MJoutput−1 per year, respectively.

Environmental evaluation and optimization of energy use and greenhouse gases mitigation for farm production systems in Mashhad, Iran.

The current paper aimed at evaluating and optimizing the efficiency of energy use and mitigation of environmental pollution by minimizing the emissions and intensity of greenhouse gases (GHG) for farm production systems in Mashhad, Iran. The results indicated that the total values of consumed energy were equal to 28,648, 38,479, and 43,490MJha-1 for barley, canola, and forage corn, respectively. The highest rate of the consumed energy for all crops belonged to irrigation electricity, diesel fuel, and nitrogen consumption. The highest and lowest energy efficiencies were respectively achieved from forage corn and canola, while barley production led to the lowest GHG emissions. The estimation of GHG intensity demonstrated that canola with 53% took up the highest intensity, which was followed by barley (30%) and forage corn (17%). Since the intensity of GHG takes into account the amount of energy produced by each crop per hectare, this index is more suitable than GHG emissions for assessing environmental pollution. The results of optimal responses of the multiple goal programming (MGP) model revealed that the optimum evaluated cultivation areas (for meeting the goals of the study) for barley and forage corn were 10,088 and 3256ha, respectively, while the MGP model generally eliminates canola from the cultivation plan. On the other hand, the plan proposed by the MGP model increases the total energy efficiency from 103,625 for the current systems to 105,169 for the optimized systems per year. Furthermore, the emissions and intensity of GHG were reduced by the model to 311,786kgCO2eq and 10kgCO2eqMJoutput-1 per year, respectively.

Analysis of Economic Value and Livestock Farming Model based on the Integration of Cattle-Palm Oil Plantation on Peatlands in Pasangkayu Regency, West Sulawesi, Indonesia

Pasangkayu Regency is one of the regencies in West Sulawesi that has the potential to apply the concept of sustainable agriculture through palm oil plantations. One of the efforts in developing sustainable farming systems is by integrating agriculture and livestock farming. The purpose of this study is to analyze the economic value and livestock model based on the integration of palm and cattle on peatlands in the Pasangkayu Regency. The study was conducted in palm oil plantations on peatlands in Pedongga District, Pasangkayu Regency from June to August 2018. Data collection techniques were carried out by interviewing and distributing questionnaires directly to 45 informants. The analysis was performed including economic analysis, analysis of sustainability data, analysis of Multiple Goal Programming (MGP), also the drafting of the index and the status of sustainability of integrated palm-cattle. The economic value of the farmers in integrated farming systems of cattle-palm on peatlands in the Pasangkayu Regency showed by the income earned was Rp. 11,069,436.18 / year and much higher than the economic value without integration which the income was only Rp. 916,982.73 / year. The integration-based livestock farming model observed from the ecological, economic, social and cultural, and the legal and institutional dimensions were categorized as sustainable, while the infrastructure and technology dimensions were still below sustainable values. Therefore, the overall integration of palm and cattle on peatlands in the Pasangkayu Regency was categorized as sustainable.

Regional Input—Output Multiple Choice Goal Programming Model and Method for Industry Structure Optimization on Energy Conservation and GHG Emission Reduction in China

To assess the potential of China’s industrial restructuring on energy conservation and greenhouse gas (GHG) emission reduction in 2020, this study proposes an input—output multi-choice goal programming model and method. In this model, the goals include the maximization of gross domestic product (GDP), minimization of energy consumption and GHG emission. They are subjected to the input—output balance, economy development, energy supply, and industry diversity. And four scenarios with different decision preferences are taken into accounted in the solutions of the industrial structure optimization model. The results demonstrate that industrial restructuring has potential in energy saving and emission reducing. First, after optimization, energy consumption intensity and GHG emission intensity can drop by 13.88246% and 5.33767% over 2012, and GDP can grow up at annual growth rate 6.6% from 2013–2020. Second, promoting the development of the low energy-intensive and low GHG emission intensive sectors is an effective method for energy conservation and emission reduction. Three, compared to energy intensity reduction, GHG emission intensity reduction is less effective for four scenarios. Four, there are several difficulties to achieve the amounts and intensity control targets of energy conservation and GHG emission reduction simultaneously. It is suggested that China had better strive to promote progress of technologies of energy conservation and GHG emission reduction while adjusting the industrial structure.

An integrated fuzzy multiple criteria supplier selection approach and its application in a welding company

Supplier selection is a strategic decision-making task for any company, as it engages multiple criteria for the evaluation and selection of alternate suppliers. So, multi-criteria decision making (MCDM) is a necessary approach in this domain. When both the qualitative and quantitative criteria are available and required to be evaluated simultaneously in decision making process for the supplier selection, a proper integrated approach is necessary to be adopted in order to select the best supplier and to find out the interrelationship structure within criteria. To address these issues, this paper proposes a unique integrated multi-attribute decision making (MADM) and mathematical programming (MP)-based model in a mixed environment (i.e., considering qualitative and quantitative criteria together) by combining decision making trial and evaluation laboratory (DEMATEL)-based on analytic network process (ANP), i.e., DANP, fuzzy technique for order of preference by similarity to ideal solution, i.e., FTOPSIS and multiple segment goal programming (MSGP). Network relationship map (NRM) is used to outline the interrelationships among the dimensions and criteria. The novelty of the proposed supplier selection approach lies with the fact that both the qualitative and quantitative criteria have been considered in it. Sensitivity analysis has also been carried out to validate the result of our proposed methodology. In addition, the result of our proposed method is supported by DANP-based fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) technique and the best supplier has been identified. Delivery schedule and environmental collaboration are revealed to be the most and least important dimensions, respectively.

Preface: Multiple criteria optimization and goal programming in science, engineering, and social sciences

Preface: Multiple criteria optimization and goal programming in science, engineering, and social sciences

Coastal Community Welfare Improvement through Optimization of Integrated Pond Farming Management in Indonesia

The lack of tenure and limited production factors causing coastal communities always be trapped on the circle of poverty, or far from prosperous. The research objective is to optimize the use of seaweed production factors that integrated with milkfish to improve the welfare of coastal communities in Indonesia. Data analysis employed Multiple Goal Programming methods. The results showed that the average of pond tenure by farmers covering 5,1 Ha with seaweed production 13,191 tons, and profits IDR76,347,700.0 per year (1USD equal to 13,000IDR). The maintenance costs of pond is the kind of production factor that limited availability, while production factors seeds, seedlings, fertilizers, and pesticides, are relatively available to farmers. Optimization results the integrated management of pond show the maximum revenue is achieved IDR1,089.89 million, labor employment 72 people, and target of seaweed production reached 188.65 tons. This means that the welfare of the farmers can be improved through the expansion of pond, and the addition of the production factor, especially capital and fertilizer.

A multiple stochastic goal programming approach for the agent portfolio selection problem

Stochastic goal programming is a suitable solution approach for multi-objective stochastic programs when a unique goal is settled for each objective function. In this paper, we address the case of multiple stochastic goals for an objective function. We derive results from studying the agent portfolio selection problem. The proposed multiple stochastic goal programming approach allows investors to set different goals for the return objective function. A chance constrained approach is proposed to address the stochastic investors’ minimum acceptable rate of return and a recourse approach to deal with investors’ ideal rate of return. An empirical study from Bahrain stock market is reported.

Optimal Production Systems in Highland Communities in Chiang Mai Province

Abstract Countries around the world are facing increasing problems related to rapid resource depletion, especially due to a reduction in highland agricultural area which affects the country's economy, society and the environment. The farmers feel pressurized to move away from traditional methods of food production in order to improve their economic well-being by switching to mono-crops with high retail values. This has also led to social changes in the highland communities as some farmers are more successful than others for a variety of reasons. The primary purpose of this study is to research agricultural production systems which are both environmentally friendly and capable of providing the farmers and their families with food security and an improved standard of living. The study area in Pang Daeng Nai Royal Project Extensions collected a sample from 185 households. The input and output prices were an average taken from the three years and the data was analyzed by a multiple goal and multi-period programming model. This aimed to optimize resource management by considering four objective goals. These were to maximize income, ensure rice sufficiency for the household consumption, to minimize chemical costs and to minimize fertilizer costs. The analysis was subject to the constraints estimated from household consumption and income levels which were used for the household consumption model. The coefficients for the main crop were estimated from the production frontier function and this resulted in a 5 year planning framework. The primary results of this analysis indicate that it is possible to reach the optimization goals. For an average farm of 17.85 rai, the study suggests that the land should be allocated as follows: 27% for rice cultivation, 46% for field crop conservation farming (maize-legume relay-cropping), 11% for perennial trees (mango), and 17% for semi-perennial crops (passion fruit). This production system can generate of 92,600 -101,400 THB per year cash income per household. This will produce on average 1,261 kilograms of rice per year per household. By following this optimal land use, it could reduce the cost of chemicals and fertilizers by 6,600 -10,200 THB per household per year. If decisions on optimal land use are done in highland community, land would be allocated to mix perennial and semi-perennial fruit trees including without waste burning from production that the optimized production plan is environmentally sustainable.

A multiple objective stochastic approach to vehicle routing problem

This research incorporates the concept of chance-constrained programming and multiple objective goal programming in the area of vehicle routing problem. The research led to the development of the model of the goal programming (GP) stochastic vehicle routing problem (SVRP) that allows decision-makers’ involvement in the solution process of problem for obtaining satisfactory solutions. Due to the complexity of the SVRP, a set of stations to be visited by a fleet of vehicles needs to be partitioned into feasible sets of routes, one for each vehicle enabling the application of the multiple objectives GP technique to each of the vehicle routes. The multiple objectives SVRP then consisted of the following two major stages: (1) route construction stage (RCS) and (2) route improvement stage (RIS). The RCS of the problem consists of the problem formulation and partitioning a set of stations into feasible sets of vehicle routes. Due to the complexity of the problem, only heuristic methods for solving SVRP are considered in this stage. On the other hand, the RIS of the problem consists of (1) problem formulation in which goals and probabilistic constraints are identified, (2) transformation of problem in (1) into an equivalent deterministic form, and (3) GP formulation of RIS in which priorities of various goals are identified. To solve the problems stated in the RCS and RIS of the problem, two interactive computer programs coded in Fortran computer language are developed. To test and validate the algorithm proposed in this research, two test problems, usually employed by other researchers, were took into consideration. A modification of the Clarke and Write algorithm is developed to determine the most favorable vehicle routes of the SVRP for the “E”-type problem. Additionally, two heuristic algorithms which are the modification of the Clarke and Wright “savings” approach are developed for solving the “F”-type problem. The E- and F-type problems are the name given to the equivalent deterministic form of the probabilistic cost minimization problem and total loading and unloading time minimization problem, respectively.

Fuzzy multiple-goal programming for analysing outsourcing cost-effectiveness in hi-tech manufacturing

Given high-tech industry trends such as limited production, diverse model range, short product life cycle, and high customer responsiveness, issues related to recognitive core vs. non-core operations in internal vs. external environments are crucial in hi-tech production systems planning. This work elucidates the relationship between capacity planning and suppliers with a focus on quantity allocation, manufacturing quantity, capacity limit, warehouse space, and time period for hi-tech production planning. A fuzzy multiple-goal programming approach is adopted to model total cost, holding cost, and rework cost in order to analyse the relative cost-effectiveness of different factors. The proposed model was examined via the fuzzy analysis of its application to an actual building-integrated photovoltaic (BIPV) manufacturer with variable characteristics. The proposed model of cost-effectiveness accommodates variables such as multiple components, quality, and responsiveness, it integrates multi-stage functions, and a specific implementation is demonstrated. Various scenarios are designed to analyse the transaction options for outsourcing under combined schemes. The analytical results in this study can help decision makers to systematically analyse the cost effectiveness of outsourcing during capacity planning in practical applications.

Special issue on developments in multiple objective programming and goal programming: theory and applications

Special issue on developments in multiple objective programming and goal programming: theory and applications

CONSERVATION DEVELOPMENT OF TIMOR DEER (Cervus timorensis) AS COMMERCIAL PURPOSE(WITH OPTIMISTIC RATE ESTIMATION)

The aim of this research was to determine the profit obtained from breeding of Timor deercommercially. This research was done in East Java. Survey method was used to answer the objective.The study location were selected by purposive sampling. Usually deer was develop in conservation area,but because the area was decrease so the number of deer also decrease. Model of deer raisingdevelopment should be improved not only for conservation but also for commercial purpose. Theoptimum deer raising were considered and monitored with a purpose to maximize commercial Timordeer by using Multiple Objective Goal Programming (MOGP) to find the Optimistic Rate Estimation.The result of this study showed to get the optimum benefit, it had to be applied together withconservation and commercial effort at the same time. Results of study showed that profit was taken fromselling velvet was 164.46%. Profits taken from selling antler was 350.56%, from selling alive deer was394.28%, from selling recreation tickets was 259.08%, from selling venison1 was 135.98%, and fromselling deer leather was 141.24%. Operational cost spent were 168.46% for feeding cost, 213.23% formaintenance cost, and 232.04% for labors’ salaries. The amount of operational cost required in MOGPmodel, with lower expenses and commercial priority were 185.54% for feeding cost, 253.13% formaintenance cost, and 246.95% for paying labors’ salaries. The MOGP model result with commercialpriority reached 335.21%, while in MOGP model with lower costs and commercial priority gave profitfor breeders up to 381.26%.

Special issue on developments in multiple objective programming and goal programming: theory and applications

Special issue on developments in multiple objective programming and goal programming: theory and applications

Special issue on recent developments in multiple objective programming and goal programming

International Transactions in Operational ResearchVolume 19, Issue 4 p. 493-494 Preface Special issue on recent developments in multiple objective programming and goal programming Taicir Loukil, Taicir Loukil Guest EditorsSearch for more papers by this authorJoão Clímaco, João Clímaco Guest EditorsSearch for more papers by this author Taicir Loukil, Taicir Loukil Guest EditorsSearch for more papers by this authorJoão Clímaco, João Clímaco Guest EditorsSearch for more papers by this author First published: 30 May 2012 https://doi.org/10.1111/j.1475-3995.2012.00855.xRead the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume19, Issue4July 2012Pages 493-494 RelatedInformation

A GOAL PROGRAMMING APPROACH TO GROUP DECISION MAKING WITH INCOMPLETE FUZZY AND INTERVAL PREFERENCE RELATIONS

In order to solve group decision making (GDM) problems where the preference relations are provided by decision makers with incomplete fuzzy and interval numbers, this paper develops a GDM approach on the basis of multiple objective optimization and goal programming methods. The proposed approach first analyzes the two types of preference relations and then builds their respective optimization models. Subsequently, an integrated programming model combining the two preference relations is developed to minimize the inconsistency among the decision makers' opinions. By solving the programming model, the ranking of alternatives or selection of the most desirable alternative can be obtained using the intermediate priority vector. Two numerical examples including incomplete fuzzy and interval preference relations are examined to illustrate and show the applicability of the proposed approach.

A Hybrid Model to Quantify the Impact of Climate Change on Agriculture in Godavari Basin, India

A hybrid model incorporating the econometric and programming models was developed to quantify the impact of climate change on agriculture in Godavari basin, India. The Just and Pope production function was used to estimate the mean yield of crops and the variance associated with the mean yield and using the estimated yield, the multiple goal programming model was used to optimize the land and water use under mid and end century climate change scenarios. The results indicated that rice production will reduce during mid and end-century periods by 16% and 36% respectively and by incorporating the water and labour saving technologies in the crop production, the reduction in rice production will be eliminated during mid-century and it will be only 19% during end-century period. The overall water saving will be about 20% due to the adoption of these technologies. Technology up-scaling programs are suggested. Areas for future research are also indicated.

An Interactive Fuzzy Goal Programming Approach for Multi-period Multi-product Production Planning Problem

This study addresses an interactive multiple fuzzy goal programming (FGP) approach to the multi-period multi-product (MPMP) production planning problem in an imprecise environment. The proposed model attempts to simultaneously minimize total production costs, rates of changes in labor levels, and maximizing machine utilization, while considering individual production routes of parts, inventory levels, labor levels, machine capacity, warehouse space, and the time value of money. Piecewise linear membership functions are utilized to represent decision maker's (DM's) overall satisfaction levels. A numerical example demonstrates the feasibility of applying the proposed model to the MPMP problem. Furthermore, the proposed interactive approach facilitates the DM with a systematic framework of decision making process which enables DM to modify the search direction to reach the most satisfactory results during solving process.