The current research concerns multiobjective linear programming problems with interval objective functions coefficients. It is known that the most credible solutions to these problems are necessarily efficient ones. T...
详细信息
The current research concerns multiobjective linear programming problems with interval objective functions coefficients. It is known that the most credible solutions to these problems are necessarily efficient ones. To solve the problems, this paper attempts to propose a new model with interesting properties by considering the minimax regret criterion. The most important property of the new model is attaining a necessarily efficient solution as an optimal one whenever the set of necessarily efficient solutions is nonempty. In order to obtain an optimal solution of the new model, an algorithm is suggested. To show the performance of the proposed algorithm, numerical examples are given. Finally, some special cases are considered and their characteristic features are highlighted.
Finding an efficient or weakly efficient solution in a multiobjective linear programming (MOLP) problem is not a difficult task. The difficulty lies in finding all these solutions and representing their structures. Si...
详细信息
Finding an efficient or weakly efficient solution in a multiobjective linear programming (MOLP) problem is not a difficult task. The difficulty lies in finding all these solutions and representing their structures. Since there are many convenient approaches that obtain all of the (weakly) efficient extreme points and (weakly) efficient extreme rays in an MOLP, this paper develops an algorithm which effectively finds all of the (weakly) efficient maximal faces in an MOLP using all of the (weakly) efficient extreme points and extreme rays. The proposed algorithm avoids the degeneration problem, which is the major problem of the most of previous algorithms and gives an explicit structure for maximal efficient (weak efficient) faces. Consequently, it gives a convenient representation of efficient (weak efficient) set using maximal efficient (weak efficient) faces. The proposed algorithm is based oil two facts. Firstly, the efficiency and weak efficiency property of a face is determined using a relative interior point of it. Secondly, the relative interior point is achieved using some affine independent points. Indeed, the affine independent property enable us to obtain an efficient relative interior point rapidly. (c) 2008 Elsevier Inc. All rights reserved.
The aim of this note is to point out and correct some errors in the definitions, notations operations and possibilistic programming model introduced by Sadi-Nezhad and Akhtari (2008) and hereby develop two correct pos...
详细信息
The aim of this note is to point out and correct some errors in the definitions, notations operations and possibilistic programming model introduced by Sadi-Nezhad and Akhtari (2008) and hereby develop two correct possibilistic programming models for fuzzy multidimensional analysis of preference in the fuzzy multiattribute group decision making problems with both the fuzzy weight vector and the fuzzy positive ideal solution (PIS) unknown a priori. (C) 2014 Elsevier Ltd. All rights reserved.
Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should...
详细信息
Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjectiveprogramming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different pi levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help the decision makers justify and/or adjust their waste management strategies based on their implicit knowledge and preferences. (c) 2012 Elsevier B.V. All rights reserved.
This paper considers multiobjective linear programming problems (MOLPP) where random fuzzy variables are contained in objective functions and constraints. A new decision making model optimizing possibilistic value at ...
详细信息
This paper considers multiobjective linear programming problems (MOLPP) where random fuzzy variables are contained in objective functions and constraints. A new decision making model optimizing possibilistic value at risk (pVaR) is proposed by incorporating the concept of value at risk (VaR) into possibility theory. It is shown that the original MOLPPs involving random fuzzy variables are transformed into deterministic problems. An interactive algorithm is presented to derive a satisficing solution for a decision maker (DM) from among a set of Pareto optimal solutions. Each Pareto optimal solution that is a candidate of the satisficing solution is exactly obtained by using convex programming techniques. A simple numerical example is provided to show the applicability of the proposed methodology to real-world problems with multiple objectives in uncertain environments. (C) 2012 Elsevier Ltd. All rights reserved.
We consider a multiobjectivelinear program. We propose a procedure for computing all additive and multiplicative (percentage) tolerance in which all the objective function coefficients may simultaneously and independ...
详细信息
We consider a multiobjectivelinear program. We propose a procedure for computing all additive and multiplicative (percentage) tolerance in which all the objective function coefficients may simultaneously and independently vary while preserving the efficiency of a given solution. For a nondegenerate basic Solution, the procedure runs ill polynomial time. (C) 2007 Elsevier B.V. All rights reserved.
We consider a multiobjectivelinear program and the coefficients of the multiobjective function are supposed to be uncertain. Let x* be an efficient point. We propose a procedure computing a tolerance for each objecti...
详细信息
We consider a multiobjectivelinear program and the coefficients of the multiobjective function are supposed to be uncertain. Let x* be an efficient point. We propose a procedure computing a tolerance for each objective function coefficient, such that all these coefficients may simultaneously and independently vary within their tolerances while preserving the efficiency of x*. If x* is a non-degenerate basic solution, then the procedure runs in a polynomial time. Our method is also applicable for the intervals of multiobjective linear programming for checking the necessary efficiency of x*, i.e. whether x* is efficient for all the realizations of interval values.
The Hunter Valley coal supply chain (HVCC) is the system of logistics facilities - principally a network of rail track and three coal handling terminals - enabling coal mined by producers in the Hunter Valley to be tr...
详细信息
ISBN:
(纸本)9780987214331
The Hunter Valley coal supply chain (HVCC) is the system of logistics facilities - principally a network of rail track and three coal handling terminals - enabling coal mined by producers in the Hunter Valley to be transported, assembled, and loaded onto ships for export. The HVCC serves around 11 producers operating through more than 30 coal load points in the Hunter Valley, transporting coal over rail track extending around 450 km inland, managed by two track owner/operators, via rolling stock from four rail haulage providers that make around 22,000 train trips for approximately 1,400 vessels per year. The HVCC now delivers around 140 million tonnes of coal per annum (Mtpa), with the port of Newcastle exporting more coal by volume than any other facility in the world. The Hunter Valley Coal Chain Coordinator P/L (HVCCC) is the organization at the heart of this logistics operation. In a landmark for collaborative logistics, the HVCCC was established by HVCC stakeholders to plan and manage the valuable shared infrastructure of the system. The HVCCC provides a range of services vital to the planning and delivery of coal through the logistics system, with its core task to improve the capacity of the coal chain through a centralised planning process. One of the key ways in which this task is achieved is through the alignment of maintenance activities. All key assets in the HVCC (e.g. rail track sections, coal stacking machinery, terminal conveyor systems) undergo regular preventive maintenance, planned well in advance. While undergoing maintenance, an asset cannot function to deliver coal (or can function only with reduced capacity), thus reducing the capacity of the system. However astute scheduling of these planned maintenance activities releases latent capacity. Such astute scheduling is referred to as capacity or maintenance alignment, and is a core function of the HVCCC. The maintenance alignment process at the HVCCC is supported by a model of the system capacity,
This paper presents a complete procedure for solving Multiple Objective linearprogramming Problems. The approach generates the whole efficient set and all extreme efficient points. The algorithm is based on a new cha...
详细信息
This paper presents a complete procedure for solving Multiple Objective linearprogramming Problems. The approach generates the whole efficient set and all extreme efficient points. The algorithm is based on a new characterization of efficient face incident to a given extreme point and the connectedness property of the set of ideal tableaux associated to a degenerated point to handle degenerated problems. A numerical example is given to illustrate the proposed algorithm.
This article considers multiobjective linear programming problems (MOLPP) where random fuzzy variables are contained in objective functions and constraints. The purpose of the proposed decision making model is to opti...
详细信息
ISBN:
(纸本)9781467317146
This article considers multiobjective linear programming problems (MOLPP) where random fuzzy variables are contained in objective functions and constraints. The purpose of the proposed decision making model is to optimize values at risk under the constraints using a necessity measure. An interacitve algorithm is constructed in order to obtain a satisficing solution for the decision maker from among a set of Pareto optimal solutions.
暂无评论