Designing and Evaluating Sustainable Logistics Networks

The objective in this paper is to shed light into the design of logistic networks balancing profit and the environment. More specifically we intend to i) determine the main factors influencing environmental performance and costs in logistic networks ii) present a comprehensive framework and mathematical formulation, based on multiobjective programming, integrating all relevant variables in order to explore efficient logistic network configurations iii) present the expected computational results of such formulation and iv) introduce a technique to evaluate the efficiency of existing logistic networks.The European Pulp and Paper Industry will be used to illustrate our findings.Eco-efficiency;Data Envelopment Analysis (DEA);Multi-Objective Programming (MOP);Supply Chain Design;Sustainable Supply Chain

Regional aspects of decision-making support for rural development in Poland

Measures for rural development should be adapted to the specific regional conditions and national programs should allow for different regional priorities. However, decision-making for policy measures often takes place under special conditions with many concerned actors, unstructured decision problems and time pressure. These conditions, decision-makers in administrations and institutions are faced with, make the formation of policy-measures for rural development a complex matter. Thus, there is the question arising how decision-makers can be supported in setting priorities for allocating budgets for policy measures among regions. Recently, multi criteria decision-making approaches are discussed to tackle these kinds of decision problems. We show exemplarily for the Polish program of rural development, how decision-making could be supported using a multi-objective programming approach. Different preferences of actors can be considered explicitly by visualizing “trade-offs” and an interactive use of the approach. For example, a political "equity" objective is implemented as a constraint in the programming approach, restricting the budget differences between regions to a defined level. By a parameterization of the bound for budget differences, the "trade-off" between three objectives is displayed and evaluated. Using the exemplary programming approach, it is shown that the objective values of the two main objectives of the PROW decline, when the budget differences between regions are restricted for pursuing a political "equity" objective.Regional Budgeting, Interactive Decision-making support, Multi-objective Programming (MOP), Community/Rural/Urban Development,

An integrated model for green partner selection and supply chain construction

Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply chain because the environmental performance of the whole supply chain is significantly affected by all its constituents. The paper presents a model for green partner selection and supply chain construction by combining analytic network process (ANP) and multi-objective programming (MOP) methodologies. The model offers a new way of solving the green partner selection and supply chain construction problem both effectively and efficiently as it enables decision-makers to simultaneously minimize the negative environmental impact of the supply chain whilst maximizing its business performance. The paper also develops an additional decision-making tool in the form of the environmental difference, the business difference and the eco-efficiency ratio which quantify the trade-offs between environmental and business performance. The applicability and practicability of the model is demonstrated in an illustration of its use in the Chinese electrical appliance and equipment manufacturing industry

Isomorphic multiplicative transitivity for intuitionistic and interval-valued fuzzy preference relations and its application in deriving their priority vectors

Intuitionistic fuzzy preference relations (IFPRs) are used to deal with hesitation while interval-valued fuzzy preference relations (IVFPRs) are for uncertainty in multi-criteria decision making (MCDM). This article aims to explore the isomorphic multiplicative transitivity for IFPRs and IVFPRs, which builds the substantial relationship between hesitation and uncertainty in MCDM. To do that, the definition of the multiplicative transitivity property of IFPRs is established by combining the multiplication of intuitionistic fuzzy sets and Tanino's multiplicative transitivity property of fuzzy preference relations (FPRs). It is proved to be isomorphic to the multiplicative transitivity of IVFPRs derived via Zadeh's Extension Principle. The use of the multiplicative transitivity isomorphism is twofold: (1) to discover the substantial relationship between IFPRs and IVFPRs, which will bridge the gap between hesitation and uncertainty in MCDM problems; and (2) to strengthen the soundness of the multiplicative transitivity property of IFPRs and IVFPRs by supporting each other with two different reliable sources, respectively. Furthermore, based on the existing isomorphism, the concept of multiplicative consistency for IFPRs is defined through a strict mathematical process, and it is proved to satisfy the following several desirable properties: weak--transitivity, max-max--transitivity, and center-division--transitivity. A multiplicative consistency based multi-objective programming (MOP) model is investigated to derive the priority vector from an IFPR. This model has the advantage of not losing information as the priority vector representation coincides with that of the input information, which was not the case with existing methods where crisp priority vectors were derived as a consequence of modelling transitivity just for the intuitionistic membership function and not for the intuitionistic non-membership function. Finally, a numerical example concerning green supply selection is given to validate the efficiency and practicality of the proposed multiplicative consistency MOP model

Managing nitrate pollution in a Tunisian irrigated area: A multi-criteria analysis approach

In Tunisia, the extension of irrigated area is justified by its important role in the development and diversification of agricultural production. Nevertheless, the strong intensification of the agricultural activities may lead to the pollution of underground water resources due to an excess use of fertilisers and other chemical products. In fact, the high nitrate concentrations observed in some Tunisian irrigated areas, are related to the excessive use of nitrate fertilizers in intensive agriculture. The objective of the present study is to implement decision-making methods allowing a better combination of factors production by optimization of an economic objective and an environmental objective. This research is based on multi-criteria modelling through the optimization of two conflict objectives: an economic objective as settled by farmer in the short or medium-run (Gross margin), and an environmental objective (nitrate pollution reduction) as a long-run objective of the decision maker in order to ensure the continuity of agriculture activities and ecosystems sustainability. Data were collected through a survey conducted in the irrigated area of Kalaât El Andalous in Tunisia with a sample containing 57 farms. Efficient solutions were obtained and compared through the "constraints", "NISE" and "compromises" methods. Main results obtained indicate a significant degree of conflict between these two objectives. Indeed the maximization of the total gross margin involves an increase in the degrees of nitrate pollution and conversely. Finally, some policy implications are presented.Nitrate pollution, environmental impact, multicriteria analysis, Environmental Economics and Policy,

New thinking of multi-objective programming with changeable space – in search of excellence

Multi-objective programming (MOP) is a branch of mathematical programming that has been widely used to deal with various practical problems. With the introduction of new technologies and business models, a paradigm shift in optimization problems is gradually taking place from fixed to flexible optimization. For example, many organizations use outsourcing or business process reengineering (BPR) to improve or upgrade their objective and technological coefficients to achieve better performance. Hence, traditional MOP models should be extended from the concept of fixed to changeable parameters, called changeable space, which includes decision space and objective space. In this paper, we propose three kinds of MOP model with changeable parameters to help decision-makers achieve the desired point (aspiration level), which is better than the ideal point

Analysis of methods for supplier selection

This work seeks to determine the criteria and methods used in the problem of selecting suppliers, thus contributing to the support of entities wishing to start a selection of suppliers more effectively. To achieve these objectives, an analysis was performed of articles that make the literature review of the methods and criteria from the year 1985 to the year 2012. With the data obtained from these reviews, it was possible to verify which are the three main methods used over the years, namely data envelopment analysis (DEA), Analytical hierarchy process (AHP) and Fuzzy set theory and the main criteria used in the selection of suppliers. In this work, we present an overview of the decision making and the methods used in multi-criteria decision making. It’s tackled the problem of supplier selection, the process of selection and the reviews of literary methods and criteria used in recent years. Finally is presented the contribution to the selection of suppliers of the study conducted during the development of this dissertation, being presented and explained the main methods of selection of suppliers as well as the criteria used.info:eu-repo/semantics/publishedVersio

Negative Total Float to Improve a Multi-Objective Integer Non-Linear Programming for Project Scheduling Compression

This paper presents Multi-Objective Integer Non-Linear Programming (MOINLP) involving Negative Total Float (NTF) for improving the basic model of Multi-Objective Programming (MOP) in case the optimization of the additional cost for Project Scheduling Compression (PSC). Using the basic MOP to solve the more complex problems is a challenging task. We suspect that Negative Total Float (NTF) having an indication to make the basic MOP to solve the more general case, both simple and complex of PSC. The purpose of this research is identifying the conflicting objectives in PSC problem using NTF and improving MOINLP by involving the NTF parameter to solve the PSC problem. The Solver Application, which is an add-in of MS Excel, is used to perform optimization process to the model developed. The results show that NTF has an important role to identify the conflicting objectives in PSC. We define NTF is an automatic maximum value of the activity duration reduction to achieve due date of PSC. Furthermore, the use of NTF as a constraint in MOINLP can solve the more general case for both simple and complex PSC problem. Base on the condition, we state that the basic MOP is still significant to solve the PSC complex problems using MOINLP as a sophisticated MOP technique

Designing and Evaluating Sustainable Logistics Networks

The objective in this paper is to shed light into the design of logistic networks balancing profit and the environment. More specifically we intend to i) determine the main factors influencing environmental performance and costs in logistic networks ii) present a comprehensive framework and mathematical formulation, based on multiobjective programming, integrating all relevant variables in order to explore efficient logistic network configurations iii) present the expected computational results of such formulation and iv) introduce a technique to evaluate the efficiency of existing logistic networks.The European Pulp and Paper Industry will be used to illustrate our findings