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multi-objective design of an organ transplant network under uncertainty

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2014年 72卷 101-124页

作者： Zahiri, B. Tavakkoli-Moghaddam, R. Mohammadi, M. Jula, P. Univ Tehran Coll Engn Sch Ind Engn Tehran Iran Simon Fraser Univ Beedie Sch Business Burnaby BC V5A 1S6 Canada

We propose a novel multi-period location-allocation model for the design of an organ transplant transportation network under uncertainty. The model consists of a bi-objective mathematical programming model that minimizes total cost and time, including waiting time in the queue for the transplant operation, while considering organs' priorities. A fuzzy multi-objective programming based approach is presented to solve the small and medium size problems to optimality. For larger problems, we propose two meta-heuristics based algorithms. Lower bounds, and several numerical examples with managerial insights are discussed. A real case-study is provided, and the existing and the proposed optimal solutions are compared. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Healthcare network multi-period organ transplant network fuzzy multi-objective programming Queuing theory Meta-heuristics

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Supply chain outsourcing risk using an integrated stochastic-fuzzy optimization approach

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INFORMATION SCIENCES 2013年 235卷 242-258页

作者： Wu, Dexiang Wu, Desheng Dash Zhang, Yidong Olson, David L. Univ Toronto Dept Mech & Ind Engn Toronto ON M5S 3G8 Canada Univ Toronto RiskLab Toronto ON M5S 3G8 Canada Univ Sci & Technol China Sch Management Hefei 230026 Anhui Peoples R China SUNY Buffalo Dept Ind & Syst Engn Buffalo NY 14260 USA Univ Nebraska Dept Management Lincoln NE 68588 USA

A stochastic fuzzy multi-objective programming model is developed for supply chain outsourcing risk management in presence of both random uncertainty and fuzzy uncertainty. Utility theory is proposed to treat stochastic data and fuzzy set theory is used to handle fuzzy data. An algorithm is designed to solve the proposed integrated model. The new model is solved using the proposed algorithm for a three stage supply chain example. Computation suggests an analysis of risk averse and procurement behavior, which indicates that a more risk-averse customer prefers to order less under uncertainty and risk. Trade-off game analysis yields supported points on the trade-off curve, which can help decision makers to identify proper weighting scheme where Pareto optimum is achieved to select preferred suppliers. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Supplier selection Supply chain risk management fuzzy multi-objective programming Utility

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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 reliability-and-cost-based fuzzy approach to optimize preventive maintenance scheduling for offshore wind farms

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 124卷 643-663页

作者： Zhong, Shuya Pantelous, Athanasios A. Goh, Mark Zhou, Jian Univ Cambridge Dept Engn Inst Mfg Cambridge CB3 0FS England Monash Univ Dept Econometr & Business Stat Clayton Vic 3800 Australia Natl Univ Singapore Logist Inst Asia Pacific Singapore 119613 Singapore Natl Univ Singapore NUS Business Sch Singapore 119613 Singapore Shanghai Univ Sch Management Dept Management Sci & Engn Shanghai 200444 Peoples R China

We study the preventive maintenance scheduling problem of wind farms in the offshore wind energy sector which operates under uncertainty due to the state of the ocean and market demand. We formulate a fuzzy multi-objective non-linear chance-constrained programming model with newly-defined reliability and cost criteria and constraints to obtain satisfying schedules for wind turbine maintenance. To solve the optimization model, a 2-phase solution framework integrating the operational law for fuzzy arithmetic and the non-dominated sorting genetic algorithm II for multi-objective programming is developed. Pareto-optimal solutions of the schedules are obtained to form the trade-offs between the reliability maximization and cost minimization objectives. A numerical example is illustrated to validate the model. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Offshore wind energy Preventive maintenance scheduling fuzzy chance-constrained programming fuzzy multi-objective programming Reliability Maintenance cost

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Mixed model disassembly line balancing problem with fuzzy goals

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第20期51卷 6082-6096页

作者： Paksoy, Turan Gungor, Askiner Ozceylan, Eren Hancilar, Arif Selcuk Univ Dept Ind Engn Konya Turkey Pamukkale Univ Dept Ind Engn Denizli Turkey

The collection of used products is the driving force of remanufacturing systems and enterprises can gain significant economic, technical and social benefits from recycling. All products are disassembled up to some level in remanufacturing systems. The best way to disassemble returned products is valid by a well-balanced disassembly line. In this paper, a mixed integer programming (MIP) model is proposed for a mixed model disassembly line balancing (MMDLB) problem with multiple conflicting objectives: (1) minimising the cycle time, (2) minimising the number of disassembly workstations and (3) providing balanced workload per workstation. In most real world MMDLB problems, the targeted goals of decision makers are frequently imprecise or fuzzy because some information may be incomplete and/or unavailable over the planning horizon. This study is the first in the literature to offer the binary fuzzy goal programming (BFGP) and the fuzzy multi-objective programming (FMOP) approaches for the MMDLB problem in order to take into account the vague aspirations of decision makers. An illustrative example based on two industrial products is presented to demonstrate the validity of the proposed models and to compare the performances of the BFGP and the FMOP approaches.

关键词： disassembly disassembly line balancing mixed model disassembly lines binary fuzzy goal programming fuzzy multi-objective programming mixed integer programming

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Bees Algorithm for constrained fuzzy multi-objective two-sided assembly line balancing problem

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OPTIMIZATION LETTERS 2012年第6期6卷 1039-1049页

作者： Tapkan, Pinar Ozbakir, Lale Baykasoglu, Adil Erciyes Univ Dept Ind Engn Kayseri Turkey Dokuz Eylul Univ Dept Ind Engn Izmir Turkey

Bees Algorithm is one of the swarm intelligence based heuristics which tries to model natural behaviour of honey bees in food foraging and used to solve optimization problems. On the other hand, Two-sided Assembly Line Balancing Problem is a generalization of simple Assembly Line Balancing Problem where different assembly tasks are carried out on the same product in parallel at both left and right sides of the line. Two-sided assembly lines are generally employed for the assembly of large-sized products such as buses and trucks. Furthermore, many real life problems contain imprecise objectives and fuzzy multi-objective programming gives an opportunity to handle such situations. In this study, Two-sided Assembly Line Balancing Problem is considered more realistically by employing positional, zoning and synchronous task constraints and by utilizing fuzzy approaches so as to maximize work slackness index and line efficiency, and minimize total balance delay. For solving this problem Bees Algorithm is used as a search mechanism for obtaining good solutions and extensive computational results are presented.

关键词： Bees Algorithm Two-sided assembly line balancing problem fuzzy multi-objective programming

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Intuitionistic fuzzy multi-objective milk-run modelling under time window constraints

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JOURNAL OF INTELLIGENT & fuzzy SYSTEMS 2022年第1期42卷 47-62页

作者： Cakir, Esra Ulukan, Ziya Kahraman, Cengiz Saglam, Canan Olcer Pak, Burcu Kuleli Pekcan, Bahadir Galatasaray Univ Dept Ind Engn Ortakoy Istanbul Turkey Istanbul Tech Univ Dept Ind Engn Besiktas Turkey Borusan Logist Kagithane Istanbul Turkey Etkin Project Management & Consultancy Kozyatagi Istanbul Turkey

Milk-run is a delivery method allowing to move small quantities of a large number of different items with predictable lead times from various suppliers to a customer. The main goal is to minimize the transportation cost by minimizing the travel distance and by maximizing vehicle capacities. The effects of uncertainties in arrival times of vehicles and loading times of shipments should also be considered in modeling the milk-run problems. In this paper, a multi-objective linear programming model, an ordinary fuzzy multi-objective linear programming model and an intuitionistic fuzzy multi-objective linear programming model are proposed for the milk-run modeling under time window constraints. The proposed approaches are applied on the real-life data of Borusan Logistics which is one of the largest logistics firms in Turkey and the results are presented.

关键词： Ordinary fuzzy set intuitionistic fuzzy set fuzzy multi-objective programming milk-run time window constraint logistic network

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A new bi-objective model of the urban public transportation hub network design under uncertainty

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ANNALS OF OPERATIONS RESEARCH 2021年第1-2期296卷 131-162页

作者： Kaveh, Firoozeh Tavakkoli-Moghaddam, Reza Triki, Chefi Rahimi, Yaser Jamili, Amin Univ Tehran Sch Ind Engn Coll Engn Tehran Iran Arts & Metier ParisTech LCFC Metz France Hamad Bin Khalifa Univ Coll Sci & Engn Doha Qatar Univ Salento Dept Engn Innovat Lecce Italy

This paper presents a new bi-objective multi-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the high construction costs of hub links in an urban public transportation network, it is not economic to create a complete hub network. Moreover, the demand is assumed to be dependent on the utility proposed by each hub. Thus, the elasticity of the demand is considered in this paper. The presented model also has the ability to compute the number of each type of transportation vehicles between every two hubs. The objectives of this model are to maximize the benefits of transportation by establishing hub facilities and to minimize the total transportation time. Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. Our experimental results demonstrated the validity of our developed model and approaches. Moreover, an intensive sensitivity analyze study is carried out on a real-case application related to the monorail project of the holy city of Qom.

关键词： Urban transportation Capacitated hub location problem Elastic demand fuzzy multi-objective programming Meta-heuristics

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

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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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Applying a fuzzy multi-objective model for a production-distribution network design problem by using a novel self-adoptive evolutionary algorithm

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS 2021年第1期8卷 1-22页

作者： Goodarzian, Fariba Hosseini-Nasab, Hassan Univ Yazd Dept Ind Engn Yazd Iran

In this paper, a new fuzzy bi-objective mathematical model for production-distribution problem under uncertainty for a four-echelon supply chain network design involving of several suppliers, producers, distributors, customers, and a set of transportation modals with different reliability rates are presented. In addition to minimise the total cost of the supply chain, the second objective is maximising reliability rate of the whole proposed system. In order to solve the proposed model, a hybrid two-phase solution procedure is proposed based on possibilistic programming, fuzzy multi-objective programming and an efficient algorithm called self-adaptive differential evolution algorithm. Finally, an extensive comparison by a set of numerical examples with different complexity along with some sensitivity analyses has been reported to explore the efficiency of proposed model as well as the performance of proposed evolutionary algorithm.

关键词： Production– distribution problem fuzzy multi-objective programming metaheuristic self-adoptive evolutionary algorithm

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