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An interval-stochastic programming based approach for a fully uncertain multi-objective and multi-mode resource investment project scheduling problem with an application to ERP project implementation

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EXPERT SYSTEMS WITH APPLICATIONS 2020年 149卷 113189-000页

作者： Subulan, Kemal Dokuz Eylul Univ Fac Engn Dept Ind Engn Izmir Turkey

Most of the real-life project scheduling cases may involve different types of uncertainties simultaneously such as randomness, fuzziness and dynamism. Based on this motivation, the present paper proposes a novel interval programming and chance constrained optimization based hybrid solution approach for a fully uncertain, multi-objective and multi-mode resource investment project scheduling problem (MRIPSP). The classical discrete-time binary integer programming formulation of the problem is extended by incorporating both the interval-valued and interval-stochastic project parameters as well as variables. In addition to the uncertain project parameters/inputs, the completion times of the activities which represent the project schedule and the availabilities of the renewable project resources are also stated as uncertain project variables and represented by interval numbers. Then, the proposed interval-stochastic multi-mode resource investment project scheduling (IS-MRIPSP) model is converted into its crisp equivalent form by using the proposed approach. The proposed approach is also able to consider different types of project scheduling risks and produces more reliable and risk-free solutions according to the project manager's attitude toward risks. Furthermore, in addition to the classical makespan objective, effective and efficient utilization of the renewable project resources, i.e., human resources, is also targeted. The efficiency and reliability factors of the human resources are also taken into consideration. In order to generate balanced project schedules which tradeoffbetween the project time and total human resource costs, compromise programming approach is adapted. Finally, in order to test the validity and practicality of the proposed approach, a real-life application is presented for an enterprise resource planning (ERP) implementation project scheduling problem of an international industrial software company. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Resource investment project scheduling interval programming Chance-constrained programming Human resource allocation ERP project management Risk attitude

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interval Goal programming Approach to Multiobjective Fuzzy Goal programming Problem with interval Weights

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Procedia Technology 2013年 10卷 587-595页

作者： Shyamal Sen Bijay Baran Pal Department of Mathematics B.K.C. College Kolkata-700108 West Bengal India Department of Mathematics University of Kalyani Kalyani-741235 West Bengal India

This article presents interval goal programming (IGP) approach for solving linear multiobjective fuzzy goal programming problem with interval weights. In the proposed approach, interval weights for achievement of fuzzy goals to their aspired levels on the basis of their relative importance are considered in an uncertain environment. In the model formulation of the problem, the membership functions for each of the fuzzy goals are defined first. Then, the membership functions are transformed into membership goals by assigning the highest membership value (unity) and introducing under-and over-deviational variables to each of them. In the solution process, the interval weights (derived from pairwise interval judgment matrix) associated with the unwanted deviational variables is introduced in the goal achievement function for minimizing them to reach the aspired goal levels of the problem. To illustrate the proposed approach, a numerical example is solved.

关键词： interval arithmetic interval programming pairwise comparison matrix fuzzy programming fuzzy goal programming goal programming

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interval Goal programming for Economic-Environmental Power Generation - Dispatch Problems

Interval Goal Programming for Economic-Environmental Power G...

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IEEE International Conference on Fuzzy Systems

作者： Bijay Baran Pal Mousumui Kumar Department of Mathematics University of Kalyani Department of Mathematics Alipurduar College

ISBN: (纸本)9781479900213

This paper presents a linear goal programming method to solve thermal power generation and dispatch problems with interval data uncertainty. In the proposed approach, the nonlinear objectives inherently involved to a problem are first transformed into their linear equivalents in the decision situation. Then, target intervals for achieving objectives are defined in power generation planning horizon. In the model formulation, the objectives with target intervals are converted into standard form of goals in goal programming methodology. In goal achievement function, both the modeling aspects of goal programming, minsum and minimax formulations, are addressed for achieving objective values within target intervals specified in the decision environment. To illustrate the potential use of the approach, the model is tested on the standard IEEE 6-Generator 30-Bus System.

关键词： Economic-environmental power generation-dispatch Goal programming interval programming Target interval Taylor Series approximation Goal programming Power production Thermoelectric power generation Dispatching Scientific notation

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End-of-life vehicles allocation management under multiple uncertainties: An interval-parameter two-stage stochastic full-infinite programming approach

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RESOURCES CONSERVATION AND RECYCLING 2016年第0期114卷 1-17页

作者： Simic, Vladimir Univ Belgrade Fac Transport & Traff Engn Vojvode Stepe 305 Belgrade 11000 Serbia

One of the main negative consequences of uncontrolled export of used vehicles from the European Union to developing countries is resource shortage for major players of European vehicle recycling systems. The resource scarcity puts serious pressure on vehicle recycling managers. An effective end-of-life vehicles (ELVs) allocation management is considered vital for mitigating the effect of the growing export of used vehicles. This paper proposes an interval-parameter two-stage stochastic full-infinite programming model for end-of-life vehicles allocation management under multiple uncertainties. A case study is conducted in order to demonstrate the potentials and applicability of the proposed model. Influences of parameter uncertainty on model solutions are thoroughly investigated. The developed model can efficiently handle uncertainties expressed as functional intervals, probability distributions and conventional crisp intervals. It is able to reduce risk of ELV management system failure due to the possible constraints violation. The formulated model can take into account connections of modeling parameters and their impact factors, thus reflecting external uncertainties of ELV management systems. It can provide a flexible ELV allocation management schemes adjustable with the variations in prices of secondary metals and end-of-life vehicles. The proposed model is able to reflect trade-off between conflicting waste management system revenues and the associated penalties for violating ELV allocation targets, thus providing a valuable insight for decision makers. (C) 2016 Elsevier B.V. All rights reserved.

关键词： End-of-life vehicle Full-infinite programming Two-stage stochastic programming interval programming Uncertainty

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Multiple objective linear programming models with interval coefficients - an illustrated overview

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第3期181卷 1434-1463页

作者： Oliveira, Carla Henggeler Antunes, Carlos INESC Coimbra Coimbra Portugal Univ Coimbra Dept Elect & Comp Engn P-3030290 Coimbra Portugal

In most real-world situations, the coefficients of decision support models are not exactly known. In this context, it is convenient to consider an extension of traditional mathematical programming models incorporating their intrinsic uncertainty, without assuming the exactness of the model coefficients. interval programming is one of the tools to tackle uncertainty in mathematical programming models. Moreover, most real-world problems inherently impose the need to consider multiple, conflicting and incommensurate objective functions. This paper provides an illustrated overview of the state of the art of interval programming in the context of multiple objective linear programming models. (C) 2006 Elsevier B.V. All rights reserved.

关键词： multiple objective linear programming interval programming satisficing approach optimizing approach

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Minimax regret solution to multiobjective linear programming problems with interval objective functions coefficients

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CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH 2013年第3期21卷 625-649页

作者： Rivaz, S. Yaghoobi, M. A. Shahid Bahonar Univ Kerman Fac Math & Comp Dept Math Kerman Iran

The current paper focuses on a multiobjective linear programming problem with interval objective functions coefficients. Taking into account the minimax regret criterion, an attempt is being made to propose a new solution i.e. minimax regret solution. With respect to its properties, a minimax regret solution is necessarily ideal when a necessarily ideal solution exists;otherwise it is still considered a possibly weak efficient solution. In order to obtain a minimax regret solution, an algorithm based on a relaxation procedure is suggested. A numerical example demonstrates the validity and strengths of the proposed algorithm. Finally, two special cases are investigated: the minimax regret solution for fixed objective functions coefficients as well as the minimax regret solution with a reference point. Some of the characteristic features of both cases are highlighted thereafter.

关键词： Multiobjective linear programming interval programming Minimax regret criterion Efficiency

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interval-parameter chance-constraint programming model for end-of-life vehicles management under rigorous environmental regulations

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WASTE MANAGEMENT 2016年 52卷 180-192页

作者： Simic, Vladimir Univ Belgrade Fac Transport & Traff Engn Vojvode Stepe 305 Belgrade 11000 Serbia

As the number of end-of-life vehicles (ELVs) is estimated to increase to 79.3 million units per year by 2020 (e.g., 40 million units were generated in 2010), there is strong motivation to effectively manage this fast-growing waste flow. Intensive work on management of ELVs is necessary in order to more successfully tackle this important environmental challenge. This paper proposes an interval-parameter chance-constraint programming model for end-of-life vehicles management under rigorous environmental regulations. The proposed model can incorporate various uncertainty information in the modeling process. The complex relationships between different ELV management sub-systems are successfully addressed. Particularly, the formulated model can help identify optimal patterns of procurement from multiple sources of ELV supply, production and inventory planning in multiple vehicle recycling factories, and allocation of sorted material flows to multiple final destinations under rigorous environmental regulations. A case study is conducted in order to demonstrate the potentials and applicability of the proposed model. Various constraint-violation probability levels are examined in detail. Influences of parameter uncertainty on model solutions are thoroughly investigated. Useful solutions for the management of ELVs are obtained under different probabilities of violating system constraints. The formulated model is able to tackle a hard, uncertainty existing ELV management problem. The presented model has advantages in providing bases for determining long-term ELV management plans with desired compromises between economic efficiency of vehicle recycling system and system-reliability considerations. The results are helpful for supporting generation and improvement of ELV management plans. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： End-of-life vehicle Management Chance-constrained programming interval programming Optimization Uncertainty

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A mathematical programming model for recycling network design under uncertainty: an interval-stochastic robust optimization model

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2014年第5-8期73卷 1057-1071页

作者： Vahdani, Behnam Naderi-Beni, Mahdi Islamic Azad Univ Qazvin Branch Fac Ind & Mech Engn Qazvin Iran Islamic Azad Univ South Tehran Branch Dept Ind Engn Tehran Iran

The development of mathematical and optimization models for reverse supply network design has concerned considerable interest over the past decades. However, the uncertainties that are inherent in the network design and the complex interactions among various uncertain parameters are challenging the capabilities of these developed tools. The aim of this paper is to propose a new mathematical programming model for recycling network design in the iron and steel industry. The considered recycling network is multi-echelon, multi-facility, multi-product, and multi-supplier. Moreover, another objective of this research is to introduce an interval-stochastic robust optimization methodology to deal with various uncertainties in the proposed model. Computational experiments are provided to demonstrate the applicability of the proposed model in recycling network design.

关键词： Location-allocationmodel Recycling networks Uncertainty interval programming Stochastic programming Robust optimization

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An approach for solving a fuzzy bilevel programming problem through nearest interval approximation approach and KKT optimality conditions

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SOFT COMPUTING 2017年第18期21卷 5515-5526页

作者： Ren, Aihong Wang, Yuping Baoji Univ Arts & Sci Dept Math Baoji 721013 Shaanxi Peoples R China Xidian Univ Sch Comp Sci & Technol Xian 710071 Shaanxi Peoples R China

In this paper, we consider a kind of bilevel linear programming problem where the coefficients of both objective functions are fuzzy numbers. In order to deal with such a problem, the original problem can be approximated by an interval bilevel programming problem in terms of the nearest interval approximation of a fuzzy number. Based on the Karush-Kuhn-Tucker (KKT) optimality conditions for the optimization problem with an interval-valued objective function, the interval bilevel programming problem can be converted into a single-level programming problem with an interval-value objective function. To minimize the interval objective function, the order relations of interval numbers are used to transform the uncertain single-objective optimization into a multi-objective optimization solved by global criteria method (GCM). Finally, illustrative numerical examples are provided to demonstrate the feasibility of the proposed approach.

关键词： Bilevel programming problem Fuzzy number interval programming Nearest interval approximation KKT conditions

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Optimal water resource planning under fixed budget by interval-parameter credibility constrained programming

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ENGINEERING OPTIMIZATION 2011年第8期43卷 879-889页

作者： Zhang, Y. M. Huang, G. H. Univ Regina Fac Engn & Appl Sci Environm Syst Engn Program Regina SK S4S 0A2 Canada

In this study, an interval credibility constrained programming (ICCP) was developed through introducing the concept of intervals into credibility constrained programming framework. interval credibility levels can help decision makers to reflect uncertainties of preferences. By ICCP, a water resource planning model with fixed fuzzy budget was developed for supporting the planning of agriculture development and environmental protection. Surface and ground water were planned for regional irrigation in wet and normal seasons. For the interval credibility preference, best and worst cases were analysed. The tradeoff between the budget and the benefit were studied by sensitive analysis. The results showed that the current water resource budget is reasonable.

关键词： water resources groundwater chance contrained programming interval programming credibility

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