Compromise Programming Method Research Articles

Designing a resilient competitive supply chain network under disruption risks: A real-world application

We address an intra-supply chain competition where a producer and resellers competing to achieve their goals, while taking into consideration the uncertainties and disruption risks. We utilize a bi-level multi-objective programming approach for designing a competitive supply chain network. A hybrid solution approach, combining the compromise programming and Benders decomposition methods, is developed to solve the model. Furthermore, an efficient inequality constraint is proposed to cope with the computational complexity of the bi-level model. To explore the practical application of the model, a real-world case example is discussed. Finally, the scalability of the solution approach is illustrated for large-scale problems.

A Fuzzy Logic Based Approach to Solve Interval Multiobjective Nonlinear Transportation Problem

This paper presents the solution procedure of multiobjective nonlinear transportation problem (MNOTP) where the cost coefficients of the objective functions, and the supply and the unknown demand parameters have been formulated as interval numbers by the decision maker. This problem has been converted into a conventional MNOTP where to minimize the interval nonlinear objective functions, the order relations that define the choice between intervals have been determined by the interval arithmetic. Also, the constraints with interval supply and unknown demand parameters have been transformed into its deterministic forms. Then the deterministic problems have been solved by two compromise programming methods. Finally, a numerical example is presented to illustrate the efficiency of the proposed procedure as well.

Selection of production lines in the metallurgical industry using the Compromise Programming method

Every organization today faces the problem of decision making. In this regard, the intent of this paper is to present an approach based on the multi-criteria decision-making methods. Primarily, the proposed approach is aimed to help solving problem of choosing the optimal production lines in the metallurgical industry. The proposed approach is based on the use of the AHP method for determining the weights of criteria, whereas the Compromise Programming is used for selection the alternatives. The usability, applicability and efficiency of the proposed approach is demonstrated in a conducted case study of selection the production lines in the metallurgical industry.

An approach for choosing the optimal route and type of transport for freight carriage using Compromise programming

This study elaborates a methodology for choosing a transport strategy based on the selection of the optimal route and type of transport. The research examines carriage by containers and includes two ways of transportation: by container block trains and by trucks. The methodology consists of three steps. The first step defines the determination of alternatives routes and criteria for assessment. Eight criteria have been studied: environmental protection; economic criteria; additional transportation fare; the duration of transportation; transhipment operations; security; reliability; stability. In the second step three approaches have been used and compared to determine the weights of the criteria: the Shannon entropy method, which is based on information from data, expert assessments by means of the Analytic hierarchy process (AHP) method and the Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The third step determines the optimal solution based on the Compromise programming method. The methodology is approbated for routes from the railway and road network of Bulgaria. The results show that the criteria with the greatest impact are: the economic criteria; the duration of transportation and environmental protection. It was found out that the technologies that include rail transport are the best variant of transportation. The presented methodology could be used for choosing transportation for other destinations in the transport network.

Optimasi Pengembangan Lahan Berbasis Daerah Irigasi di Provinsi Sulawesi Selatan

Ketahanan pangan menjadi isu strategis ketika dihubungkan dengan kenaikan jumlah penduduk dan tingginya laju konversi lahan beririgasi menjadi daerah pemukiman/industri. Peningkatan produksi padi nasional menjadi salah satu kunci pemerintah dalam pemenuhan kebutuhan pangan nasional. Pemetaan zonasi potensi pengembangan lahan irigasi telah dilakukan namun untuk menentukan kebijakan pengembangan lahan diperlukan analisa lanjut terhadap kenaikan produksi dan investasi biaya guna mengetahui efektifitas pengembangannya. Penelitian ini dilakukan guna mendapatkan skenario terbaik dalam upaya meningkatkan produksi beras nasional melalui ekstensifikasi maupun intensifikasi, serta menghitung nilai minimum investasi yang diperlukan untuk meningkatkan produksi tersebut. Penelitian dibatasi pada analisa berbasis daerah irigasi, dimana penentuan lokasi penelitian berdasarkan peta zonasi potensi pengembangan lahan irigasi dan simulasi pengelompokan produksi padi nasional. Optimasi dilakukan dengan Multi Criteria Decision Analysis (MCDA) metode Analitycal Hierarchy Process (AHP) untuk pembobotan, dilanjutkan dengan metode Compromise Programming dan Promethee untuk menentukan prioritas pengembangan. Hasil kajian menunjukkan bahwa Program Ekstensifikasi dapat menjadi prioritas pengembangan irigasi sebagai dukungan terhadap ketahanan pangan nasional. Total investasi biaya yang dikeluarkan untuk ekstensifikasi lahan irigasi rata-rata diperkirakan Rp 105,6 Juta/ha, yang dapat digunakan sebagai dasar penganggaran penentuan lahan pengembangan lahan irigasi kedepan, dengan kenaikan produksi yang dihasilkan dari ekstensifikasi lahan irigasi di Provinsi Sulawesi Selatan ini adalah 5,02 ton/ha, atau harga investasi per produksi untuk ekstensifikasi lahan irigasi ini adalah Rp 10,51 juta/ton.

A Compromise Decision-making Model for Multi-objective Large-scale Programming Problems with a Block Angular Structure under Uncertainty

This paper proposes a compromise model, based on the technique for order preference through similarity ideal solution (TOPSIS) methodology, to solve the multi-objective large-scale linear programming (MOLSLP) problems with block angular structure involving fuzzy parameters. The problem involves fuzzy parameters in the objective functions and constraints. This compromise programming method is based on the assumption that the optimal alternative is closer to fuzzy positive ideal solution (FPIS) and at the same time, farther from fuzzy negative ideal solution (FNIS).An aggregating function that is developed from LP- metric is based on the particular measure of ‘‘closeness” to the ‘‘ideal” solution.An efficient distance measurement is utilized to calculate positive and negative ideal solutions. The solution process is as follows: first, the decomposition algorithm is used to divide the large-dimensional objective space into a two-dimensional space. A multi-objective identical crisp linear programming is derived from the fuzzy linear model for solving the problem. Then, a single-objective large-scale linear programming problem is solved to find the optimal solution. Finally, to illustrate the proposed method, an illustrative example is provided.

Hazardous Materials Transportation with Multiple Objectives: A Case Study in Taiwan

Hazardous material (hazmat) transportation has been an important issue for handling hazardous materials, such as gases and chemical liquids. In the past, researchers have made great efforts to develop policies and route planning methods for hazmat transportation problems. In 2014, Kaohsiung City in Taiwan suffered a gas pipeline explosion at midnight; 32 people were killed, and hundreds of people were injured. After the incident, policies and routing strategies for hazardous materials (hazmat) transportation in Kaohsiung were initiated to avoid pipeline transportation. Although methodologies for hazmat transportation have been proposed and implemented to minimize potential risks, multiple objectives need to be considered in the process to facilitate hazmat transportation in Taiwan. In order to consider both government and operators’ aspects, a multi-objective formulation for the hazmat problem is proposed and a compromise programming method is applied to solve the problem with two objectives: travel cost and risk. The path risk is defined based on risk assessment indexes, such as road characteristics, population distribution, link length, hazardous material characteristics, and accident rates. An aggregate risk indicator is proposed for roadway segments. The compromise programming approach is developed from the concept of compromise decision and the main idea is to search the compromise solution closest to the ideal solution. The proposed method is applied to Kaohsiung City, Taiwan. The results show that two conflicting objectives keep making trade-offs between each other until they finally reach a compromise solution.

Practices and perceptions on water resource sustainability in ecovillages

AbstractIn many areas of the world, groups of people have attempted to create urban landscapes that follow the principles of environmental sustainability. To this end, groups have devised alternative models, such as ecovillages, where low‐impact handling is used and a way of life different from that of large population centers is adopted. Although these villages exist, their efficiency in the conservation of natural resources has not been effectively evaluated. This study evaluated the practices used by two Brazilian ecovillages to conserve water resources to assess whether this new concept of living is indeed successful in meeting sustainability goals. We selected 25 indicators of water sustainability, and using the compromise programming method, we quantified the distance between those landscapes self‐referenced as sustainable and an ideal hypothetical scenario. We also interpreted the communities perceptions using the distance between the current situations and the envisioned scenario. We concluded that both ecovillage are far from technically ideal scenario, but the communities have a strong sense of their limitations in implementing water resources conservation. The communities attributed this fact primarily to deficiencies in the shared management.

Optimal allocation of regional water resources: From a perspective of equity–efficiency tradeoff

Because of the significant impact on economic development, social stability, and ecological balance, the allocation of water resources has become an issue of worldwide concern. Therefore, the efficient, equitable, and sustainable allocation of water is vital for water management authorities. With sustainability (guaranteeing the minimum ecological water needs) as the constraint, the paper aims to enhance the water management by considering equity and efficiency. A multi-objective programming model is built with the first objective being to maximize the economic benefit efficiency to allow for the development of improved water allocation strategies and with the second objective being to maximize water allocation equity (measured using the Gini coefficient). A Compromise Programming (CP) method is employed to trade off economic benefit efficiency and equity in the water allocation, which can provide relatively flexible choices and trade-offs according to the decision makers’ preferences. The presented model is applied to the Qujiang river basin in China as a case study to demonstrate its feasibility, validity, and practicality, the results from which indicate the trade-off between equity and economic benefit efficiency in the model was feasible, and the conclusions are that river basin authorities need to take measures to decrease the rate of water loss and increase the available water to enhance water allocation efficiency and equity.

Optimal design model for a fixed layout storm water network

This paper focuses on finding the best solution out of the given set of alternatives, i.e., design solutions, performance of each being evaluated assigning membership value for the individual pipe as well as the network as a whole using fuzzy set theory, fulfilling ten different criteria. Different weights are applied to the criterion by five decision makers, based on the methodology of analytical hierarchical process (AHP) and document the impact of the sensitivity of weights on the outcome with values of consistency ratio below 0.1. Alternatives are ranked using distance-based compromise programming (CP) method for a given layout of storm drainage pipe network. Results of multi-criteria decision analysis (MCDA) using different weights are then compared using group decision theory to finalise the best possible alternative out of the given sets.

Optimal design model for a fixed layout storm water network

This paper focuses on finding the best solution out of the given set of alternatives, i.e., design solutions, performance of each being evaluated assigning membership value for the individual pipe as well as the network as a whole using fuzzy set theory, fulfilling ten different criteria. Different weights are applied to the criterion by five decision makers, based on the methodology of analytical hierarchical process (AHP) and document the impact of the sensitivity of weights on the outcome with values of consistency ratio below 0.1. Alternatives are ranked using distance-based compromise programming (CP) method for a given layout of storm drainage pipe network. Results of multi-criteria decision analysis (MCDA) using different weights are then compared using group decision theory to finalise the best possible alternative out of the given sets.

EVALUATING PARETO FRONT WITH TOPSIS AND FUZZY TOPSIS FOR LITERACY RATES IN ODISHA

In engineering design and manufacturing, conflicting disciplines and technologies are always involved in the design process. Decision making is the process of finding the best option among the feasible alternatives. Multi Criteria Decision Making (MCDM) methods can help decision makes to effectively deal with such situation and make wise design decision to produce an optimized design. There are varieties of existing MCDM methods, thus the selection of the most appropriate method is critical since the use of inappropriate methods often causes misleading decision process. The MCDM methods are based on aggregating function representing closeness to ideal, TOPSIS is one of the most efficient methods. And also it can be fuzziffied which gives rise to a new method called Fuzzy TOPSIS. Fuzzy TOPSIS is a new method for MCDM and very easy to understand and it is originated in the compromise programming method. Here we have adapted the Fuzzy TOPSIS method and we have arranged the multiple numbers of criteria using Knapsack algorithm and Pareto Front with the help of non dominated sorting method. Then we have ranked all the alternatives with classical Fuzzy TOPSIS method. In this paper the literacy rate of Odisha (a state of India) has been analyzed by using normal TOPSIS and fuzzy TOPSIS methods and the comparative results are given. The data sets considered in this paper are the real time data given by National Census (20002013).

GIS – based multicriteria decision analysis for the delimitation of an agricultural perimeter irrigated with treated wastewater

Treated wastewater resource is underexploited in Cebala’s Irrigated scheme (Northern Tunisia) and farmers are reluctant to reuse it. The delimitation of the irrigated area will help enhance the global economic profitability of the perimeter not only by reducing the operation and maintenance costs but also by optimizing the reuse activity according to the farmers’ demands, their aspirations and aims. Thus, the aim of this paper is to consider reducing the surface of the irrigated area, keeping only the parcels where the resource is highly demanded. A spatial data analysis using a multicriteria decision technique (compromise programming—CP) and a geographical information system was carried out to choose the best scenario. To this end, five zones where breeding activity is well developed and the non-conventional resource highly demanded were identified as the closest delimitations to the ideal solution.The Compromise programming method was used to rank these solutions. Finally, a surface of 2485ha was identified as the best delimitation scenario, corresponding to the area where breeding activity is well developed.

EVALUATING PARETO FRONT WITH TOPSIS AND FUZZY TOPSIS FOR LITERACY RATES IN ODISHA

In engineering design and manufacturing, conflicting disciplines and technologies are always involved in the design process. Decision making is the process of finding the best option among the feasible alternatives. Multi Criteria Decision Making (MCDM) methods can help decision makes to effectively deal with such situation and make wise design decision to produce an optimized design. There are varieties of existing MCDM methods, thus the selection of the most appropriate method is critical since the use of inappropriate methods often causes misleading decision process. The MCDM methods are based on aggregating function representing closeness to ideal, TOPSIS is one of the most efficient methods. And also it can be fuzziffied which gives rise to a new method called Fuzzy TOPSIS. Fuzzy TOPSIS is a new method for MCDM and very easy to understand and it is originated in the compromise programming method. Here we have adapted the Fuzzy TOPSIS method and we have arranged the multiple numbers of criteria using Knapsack algorithm and created a Pareto Front with the help of non-dominated sorting method. Then we have ranked all the alternatives with classical Fuzzy TOPSIS method. In this paper the literacy rate of Odisha (a state of India) has been analyzed by using normal TOPSIS and fuzzy TOPSIS methods and the comparative results are given. The data sets considered in this paper are the real time data given by National Census (20002013).

A cognitive approach for the multi-objective optimization of RC structural problems

This paper proposes a cognitive approach for analyzing and reducing the Pareto optimal set for multi-objective optimization (MOO) of structural problems by means of jointly incorporating subjective and objective aspects. The approach provides improved knowledge on the decision-making process and makes it possible for the actors involved in the resolution process and its integrated systems to learn from the experience. The methodology consists of four steps: (i) the construction of the Pareto set using MOO models; (ii) the filtering of the Pareto set by compromise programming methods; (iii) the selection of the preferred solutions, utilizing the relative importance of criteria and the Analytic Hierarchy Process (AHP); (iv) the extraction of the relevant knowledge derived from the resolution process. A case study on the reinforced concrete (RC) I-beam has been included to illustrate the methodology. The compromise solutions are obtained through the objectives of economic feasibility, structural safety, and environmental sustainability criteria. The approach further identifies the patterns of behavior and critical points of the resolution process which reflect the relevant knowledge derived from the cognitive perspective. Results indicated that the solutions selected increased the number of years of service life. The procedure produced durable and ecological structures without price trade-offs.

Simulation and experimental validation of powertrain mounting bracket design obtained from multi-objective topology optimization

A framework of multi-objective topology optimization for vehicle powertrain mounting bracket design with consideration of multiple static and dynamic loading conditions is developed in this article. Incorporating into the simplified isotropic material with penalization model, compromise programming method is employed to describe the multi-objective and multi-stiffness topology optimization under static loading conditions, whereas mean eigenvalue formulation is proposed to analyze vibration optimization. To yield well-behaved optimal topologies, minimum member size and draw constraint are settled for meeting manufacturing feasibility requirements. The ultimate mounting bracket is reconstructed based on the optimum results. Numerical analyses of the bracket are performed, followed by physical tests. It is proven that topology optimization methodology is promising and effective for vehicle component design.

Advantages of integrated and sustainability based assessment for metabolism based strategic planning of urban water systems

Despite providing water-related services as the primary purpose of urban water system (UWS), all relevant activities require capital investments and operational expenditures, consume resources (e.g. materials and chemicals), and may increase negative environmental impacts (e.g. contaminant discharge, emissions to water and air). Performance assessment of such a metabolic system may require developing a holistic approach which encompasses various system elements and criteria. This paper analyses the impact of integration of UWS components on the metabolism based performance assessment for future planning using a number of intervention strategies. It also explores the importance of sustainability based criteria in the assessment of long-term planning. Two assessment approaches analysed here are: (1) planning for only water supply system (WSS) as a part of the UWS and (2) planning for an integrated UWS including potable water, stormwater, wastewater and water recycling. WaterMet2 model is used to simulate metabolic type processes in the UWS and calculate quantitative performance indicators. The analysis is demonstrated on the problem of strategic level planning of a real-world UWS to where optional intervention strategies are applied. The resulting performance is assessed using the multiple criteria of both conventional and sustainability type; and optional intervention strategies are then ranked using the Compromise Programming method. The results obtained show that the high ranked intervention strategies in the integrated UWS are those supporting both water supply and stormwater/wastewater subsystems (e.g. rainwater harvesting and greywater recycling schemes) whilst these strategies are ranked low in the WSS and those targeting improvement of water supply components only (e.g. rehabilitation of clean water pipes and addition of new water resources) are preferred instead. Results also demonstrate that both conventional and sustainability type performance indicators are necessary for strategic planning in the UWS.

Farmer’s subjective elicited water response function for intensive olives and compromise programming method for irrigation supply decision

This research analyses the subjective crop yield-water relationship and proposes a method to determine water supply in irrigated olives. The probability density for water response functions (PDF) is elicited from a series of interviews carried out on a wide group of farmers. The elicitation technique is based upon the triangular distribution (highest possible, most frequent and lowest possible) and estimates of yield related to water supply (low, ‘normal’ and full irrigation). The model presented illustrates the possibility of implementing simple decision models to support farmers to manage water considering the objectives of maximizing profit and minimizing risk.

A New Compromise Decision-making Model Based on TOPSIS and VIKOR for Solving Multi-objective Large-scale Programming Problems with a Block Angular Structure under Uncertainty

This paper proposes a compromise model, based on a new method, to solve the multi-objective large-scale linear programming (MOLSLP) problems with block angular structure involving fuzzy parameters. The problem involves fuzzy parameters in the objective functions and constraints. In this compromise programming method, two concepts are considered simultaneously. First of them is that the optimal alternative is closer to fuzzy positive ideal solution (FPIS) and farther from fuzzy negative ideal solution (FNIS). Second of them is that the proposed method provides a maximum ‘‘group utility’’ for the ‘‘majority’’ and a minimum of an individual regret for the ‘‘opponent’’. In proposed method, the decomposition algorithm is utilized to reduce the large-dimensional objective space. A multi objective identical crisp linear programming derived from the fuzzy linear model for solving the problem. Then, a compromise solution method is applied to solve each sub problem based on TOPSIS and VIKOR simultaneously. Finally, to illustrate the proposed method, an illustrative example is provided.

Multi-item fuzzy-stochastic supply chain models for long-term contracts with a profit sharing scheme

In this study, we develop multi-item multi-objective manufacturer–retailer supply chain models with risk and budget constraints for long-term contracts with a profit sharing scheme in a fuzzy-stochastic environment. The manufacturing costs of the items are fuzzy and the demands for the items are random during each period. We examine two separate models with crisp and probabilistic budget constraints for long-term contracts where the business relationship is repeated, while demand is uncertain in a stochastic sense. The models are formulated as profit maximization problems. Next, the fuzzy compromise programming method, global criteria method, and weighted sum method are used to reduce the multi-objective problems into their corresponding single objective problems. Finally, the problems are solved using a gradient-based nonlinear programming technique: the generalized reduced gradient method. The models are illustrated with numerical examples for different types of stochastic demand and a comparative study is presented.