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Reliable design of a forward/reverse logistics network under uncertainty: A robust-M/M/c queuing model

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2012年第6期48卷 1152-1168页

作者： Vahdani, Behnam Tavakkoli-Moghaddam, Reza Modarres, Mohammad Baboli, Armand Univ Tehran Coll Engn Dept Ind Engn Tehran Iran Sharif Univ Technol Dept Ind Engn Tehran Iran DISP Lab Lyon 2INSA F-69621 Villeurbanne France

This paper presents a novel model for designing a reliable network of facilities in closed-loop supply chain under uncertainty. For this purpose, a bi-objective mathematical programming formulation is developed which minimizes the total costs and the expected transportation costs after failures of facilities of a logistics network. To solve the model, a new hybrid solution methodology is introduced by combining robust optimization approach, queuing theory and fuzzy multi-objective programming. Computational experiments are provided for a number of test problems using a realistic network instance. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Closed-loop supply chain (CLSC) Reliability Robust optimization Queuing theory fuzzy multi-objective programming

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Transportation planning with modified S-curve membership functions using an interactive fuzzy multi-objective approach

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APPLIED SOFT COMPUTING 2011年第2期11卷 2656-2663页

作者： Peidro, David Vasant, Pandian Univ Politecn Valencia Res Ctr Prod Management & Engn CIGIP Valencia Spain Univ Teknol PETRONAS Fundamental & Appl Sci Dept Petronas Malaysia

In this paper, we consider the transportation planning decision (TPD) problem with fuzzy goals, available supply and forecast demand. An interactive method is designed for solving the multi-objective TPD problem where the fuzzy data are represented by modified S-curve membership functions. The proposed method attempts to simultaneously minimize the total production and transportation costs and the total delivery time with reference to budget constraints and available supply, machine capacities at each source, as well as forecast demand and warehouse space constraints at each destination. An interactive fuzzy approach is applied to solve the multi-objective TPD problem and to find a preferred compromise solution. Finally, the performance of S-curve membership functions that represent uncertainty goals and constraints in TPD problems with linear membership functions in an industrial case is compared. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Transportation planning S-curve membership function fuzzy multi-objective programming

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Application of fuzzy multi-objective programming approach to supply chain distribution network design problem

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5th Mexican International Conference on Artificial Intelligence (MICAI 2006)

作者： Selim, Hasan Ozkarahan, Irem Dokuz Eylul Univ Dept Ind Engn TR-35100 Izmir Turkey

ISBN: (纸本)9783540490265

A supply chain distribution network design model is developed in this paper. The goal of the model is to select the optimum numbers, locations and capacity levels of plants and warehouses to deliver the products to the retailers at the least cost while satisfying the desired service level. Maximal covering approach is employed in statement of the service level. Different from the previous researches in this area, coverage functions which differ among the retailers according to their service standard requests are defined for the retailers. Additionally, to provide a more realistic model structure, decision maker's imprecise aspiration levels for the goals, and demand uncertainties are incorporated into the model through fuzzy modeling approach. Realistic computational experiments are provided to confirm the viability of the model.

关键词： fuzzy multi-objective programming supply chain distribution network design

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Balancing fuzzy multi-objective two-sided assembly lines via Bees Algorithm

Balancing fuzzy multi-objective two-sided assembly lines via...

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1st International Symposium on fuzzy Systems

作者： Ozbakir, Lale Tapkan, Pinar Erciyes Univ Dept Ind Engn Kayseri Turkey

Many real life problems contain imprecise variables, constraints and objectives. fuzzy set theory gives an opportunity to handle imprecise terms in such situations. Two-sided assembly line balancing (2sALB) problem which is a generalization of the well known simple assembly line balancing problem can also be modeled more realistically by employing fuzzy approaches. Such an approach is presented in this study to model and solve 2sALB problem by employing fuzzy mathematical programming and Bees Algorithm (BA). 2sALB problem is a combinatorial complex problem. For this reason BA is employed as a search mechanism for obtaining good solutions to it. BA is a relatively new member of swarm intelligence based meta-heuristics that tries to mimic natural behavior of real honey bees in food foraging in solving complex optimization problems. BA is generally applied to continuous optimization in the literature. Its application to combinatorial problems is rare. This study also presents one of the first application of BA to an assembly line balancing problem which is member of combinatorial optimization.

关键词： fuzzy multi-objective programming two-sided assembly line balancing problem Bees Algorithm soft computing

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Genetic algorithm-based fuzzy multi-objective programming approach to optimal allocation of environmental water requirements in rivers

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Gaojishu Tongxin/Chinese High Technology Letters 2006年第10期16卷 1077-1081页

作者： Yang, Wei Sun, Dezhi School of Municipal and Environmental Engineering Harbin Institute of Technology Harbin 150090 China

A fuzzy multi-objective-programming model was presented to determine appropriate environmental flow allocation for polluted urban rivers, in which the objectives included the maximization of assimilative capacity in the river, the minimization of water amount for allocation and the minimization of cost for water allocation. An integrated nonlinear fuzzy membership function, which represents a broader implication in fuzzy decision-making, was regarded as the general objective and the genetic algorithm became an essential tool in search for the global optimal solution. A case study of optimal allocation for environmental water requirements in the Liming River Basin and Daqing City demonstrates the capability of the fuzzy multi-objective model based on fuzzy decision theories to work suitably in water environmental management in a river basin.

关键词： Environmental water requirements Flow allocation fuzzy multi-objective programming Genetic algorithm

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multi-choice multi-objective linear programming problem

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JOURNAL OF INTERDISCIPLINARY MATHEMATICS 2009年第5期12卷 606-636页

作者： Biswal, M. P. Acharya, Srikumar Indian Inst Technol Dept Math Kharagpur 721302 W Bengal India

We consider a multi-objective linear programming problem where some of the right hand side parameters of the constraints are multi-choice in nature. For some right hand side parameters of the constraints, there may exist multiple choices, out of which exactly one is to be chosen. The selection from the sets should be in such a manner that the combination of choices for each set should provide best compromise solution. In order to solve the proposed multi-choice multi-objective linear programming problem, this paper proposes an equivalent mathematical model, which can be solved with the help of existing non-linear programming method. The proposed model can accommodate a maximum of sixteen choices for a single parameter. An illustrative example is presented in support of the proposed model.

关键词： multi-objective linear programming fuzzy multi-objective programming multi-choice programming non-linear programming

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Water quality management of a stretch of river Yamuna: An interactive fuzzy multi-objective approach

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WATER RESOURCES MANAGEMENT 2007年第2期21卷 515-532页

作者： Singh, Ajit Pratap Ghosh, S. K. Sharma, Pankaj BITS Civil Engn Grp Pilani 333031 Rajasthan India BITS Math Grp Pilani Rajasthan India

This paper presents an Interactive fuzzy multi-objective Linear programming (IFMOLP) model for water quality management in a river basin. The IFMOLP model formulated will first evaluate dissolved oxygen (DO) concentrations or DO deficits at a point in different reaches depending on the overall Biochemical Oxygen Demand (BOD) concentration present in the respective drain. Subsequently, the model incorporates the aspirations and conflicting objectives of the decision maker (DM) by taking into consideration the aspects relevant for pollution control boards as well as dischargers responsible for generating wastewater. The uncertainty associated with specifying the water quality criteria (based on DO concentration or DO deficit) and treatment cost to remove pollution level is incorporated by interacting the decision maker. In this process DM is asked to specify the reference aspiration levels of achievement for the values of all membership functions generated with respect to each objective. This provides flexibility for the pollution control authorities and dischargers to specify their aspirations. IFMOLP model developed herein is then used in a case study for the evaluation of optimal BOD removal in different drains located across the river Yamuna at New Delhi, India. The presented model will simulate the allocation of waste load efficiencies with satisfactory results which will indicate usefulness of the model in managing more complex river basins along with better flexible policies of water management.

关键词： water quality management Yamuna river basin fuzzy multi-objective programming optimization dissolved oxygen (DO) biochemical oxygen demand (BOD) pollution

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Method for solving quasi-concave and non-concave fuzzy multi-objective programming problems

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fuzzy SETS AND SYSTEMS 2001年第2期122卷 205-227页

作者： Yu, CS Li, HL Shih Chien Univ Dept Informat Management Taipei 10497 Taiwan Natl Chiao Tung Univ Inst Informat Management Hsinchu 30050 Taiwan

This paper proposes a method based on linear programming techniques to treat quasi-concave and non-concave fuzzy multi-objective programming (FMOP) problems. The proposed method initially presents a piecewise linear expression to interpreting a quasi-concave membership function. Then we find the convex-type break points acid transform all quasi-concave membership functions into concave functions. After that, the converted program is solved by linear programming techniques to obtain a global optimum. Tn addition to not containing any of the zero-one variables, the proposed method does not require dividing the quasi-concave FMOP problem into large sub-problems as in conventional methods. The extension of the proposed method can treat general non-concave FMOP problems by merely adding less number of zero-one variables. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： fuzzy multi-objective programming linear programming non-concave piecewise

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Optimal expansion of water quality monitoring network by fuzzy optimization approach

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2004年第1-3期91卷 145-170页

作者： Ning, SK Chang, NB Kun Shan Univ Technol Dept Environm Engn Tainan Taiwan Texas A&M Univ Dept Environm Engn Kingsville TX USA

River reaches are frequently classified with respect to various mode of water utilization depending on the quantity and quality of water resources available at different location. Monitoring of water quality in a river system must collect both temporal and spatial information for comparison with respect to the preferred situation of a water body based on different scenarios. Designing a technically sound monitoring network, however, needs to identify a suite of significant planning objectives and consider a series of inherent limitations simultaneously. It would rely on applying an advanced systems analysis technique via an integrated simulation-optimization approach to meet the ultimate goal. This article presents an optimal expansion strategy of water quality monitoring stations for fulfilling a long-term monitoring mission under an uncertain environment. The planning objectives considered in this analysis are to increase the protection degree in the proximity of the river system with higher population density, to enhance the detection capability for lower compliance areas, to promote the detection sensitivity by better deployment and installation of monitoring stations, to reflect the levels of utilization potential of water body at different locations, and to monitor the essential water quality in the upper stream areas of all water intakes. The constraint set contains the limitations of budget, equity implication, and the detection sensitivity in the water environment. A fuzzy multi-objective evaluation framework that reflects the uncertainty embedded in decision making is designed for postulating and analyzing the underlying principles of optimal expansion strategy of monitoring network. The case study being organized in South Taiwan demonstrates a set of more robust and flexible expansion alternatives in terms of spatial priority. Such an approach uniquely indicates the preference order of each candidate site to be expanded step-wise whenever the budget limit

关键词： environmental systems analysis fuzzy multi-objective programming monitoring network river basin planning water quality management

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A study of an interactive fuzzy multi-objective optimal power flow

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Electrical Engineering in Japan 1999年第1期130卷

作者： Junji Kubokawa Yoshito Okubo Hiroshi Sasaki Ryuichi Yokoyama Hiroshima University Japan Tokyo Metropolitan University Japan

As the necessity of high-quality electric power supply increases, it has been required to develop sophisticated power system operations in which several requirements stemming from economy, security, and environmental aspects are simultaneously satisfied. In general, a problem of satisfying several noncommensurable criteria is called a multiobjective optimization problem. Although the most powerful means to obtain desirable system operations is optimal power flow (OPF), a straightforward application of the conventional OPF optimizes only one objective and the remaining objectives must be treated as constraints. However, since such objectives are in trade-off relationships with each other, it is necessary to develop an efficient multiobjective OPF. In this paper, we propose a solution method of multiobjective OPF by means of fuzzy coordination. In the first step, the degree of Decision Maker (DM) satisfaction on each objective would be maximized with a prespecified membership function. The membership function would be updated in accordance with the DM's preference information and target value of the objective function. The degree of satisfaction will be improved step by step by updating the membership functions. Finally, the satisficing solution for the DM would be obtained. The proposed method has been applied to the IEEE 57 and 118 test systems, producing successful results. © 1999 Scripta Technica, Electr Eng Jpn, 130(1): 59–67, 2000

关键词： fuzzy multi-objective programming optimal power flow calculation method OPF

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