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Relief supply collaboration for emergency logistics responses to large-scale disasters

TRANSPORTMETRICA A-TRANSPORT SCIENCE 2015年第3期11卷 210-242页

作者： Sheu, Jiuh-Biing Pan, Cheng Natl Taiwan Univ Dept Business Adm Taipei 106 Taiwan

This paper proposes a novel relief supply collaboration approach to address the issue of post-disaster relief supply-demand imbalance in emergency logistics (EL) operations. This proposed approach involves two levels of recursive functions: (1) a two-stage relief supplier clustering mechanism for time-varying multi-source relief supplier selection and (2) the use of stochastic dynamic programming model to determine a multi-source relief supply that minimises the impact of relief supply-demand imbalance during EL response. The distinctive features of this proposed approach are to identify the potential relief suppliers and to minimise the imbalanced supply-demand impact under relief supply collaboration. Scenario design and model tests are conducted to demonstrate that relief supply collaboration with grouped relief suppliers has a significant benefit of alleviating the impact of imbalanced relief supply-demand, relative to collaboration with ungrouped ones.

关键词： relief supplier selection relief supply-demand imbalance stochastic programming model fuzzy clustering emergency logistics

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A stochastic programming approach to determine robust delivery profiles in area forwarding inbound logistics networks

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OR SPECTRUM 2013年第4期35卷 807-834页

作者： Schoeneberg, Tim Koberstein, Achim Suhl, Leena Univ Paderborn D-33098 Paderborn Germany Goethe Univ Frankfurt D-60323 Frankfurt Germany

One technique to coordinate the suppliers' and the producers' production plans in a supply chain is the use of delivery profiles, which provide fixed delivery frequencies for all suppliers. The selection of a delivery profile assignment has major effects on the cost efficiency and the robustness of a supply chain and thus should be performed carefully. In this work, we consider planning approaches to select delivery profiles for the case of area forwarding-based inbound logistics networks, which are commonly used in several industries to consolidate supplies in an early stage of transport. We present a two-stage stochastic mixed integer linear programming model to determine robust delivery profile assignments under uncertain and infrequent demands and complex tariff systems. The model is embedded into a solution framework consisting of scenario generation and reduction techniques, a decomposition approach, a genetic algorithm, and a standard MILP solver. On the basis of an industrial case study, we show that our approach is computationally feasible and that the planning solutions obtained by our model outperform both a deterministic approach and the planning methodology prevailing in industrial practice.

关键词： Procurement planning Delivery profiles Automotive industry stochastic programming model

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Solving a bi-objective cell formation problem with stochastic production quantities by a two-phase fuzzy linear programming approach

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2012年第5-8期58卷 709-722页

作者： Rabbani, Masoud Jolai, Fariborz Manavizadeh, Neda Radmehr, Farzad Javadi, Babak Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

We propose a bi-objective cell formation problem with demand of products expressed in a number of probabilistic scenarios. To deal with the uncertain demand of products, a framework of two-stage stochastic programming model is presented. The proposed model considers minimizing the sum of the miscellaneous costs (machine constant cost, expected machine variable cost, cell fixed-charge cost, and expected intercell movement cost) and expected total cell loading variation. Because of conflicting objectives, we develop a two-phase fuzzy linear programming approach for solving bi-objective cell formation problem. To show the effectiveness of the proposed approach, numerical examples are solved and the results are compared with the two existing approaches in the literature. The computational results show that the proposed fuzzy method achieves lower objective functions as well as higher satisfaction degrees.

关键词： Cellular manufacturing design Cell formation problem Multi-objective Fuzzy linear programming stochastic programming model

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Inventory policies for humanitarian aid during hurricanes

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Socio-Economic Planning Sciences 2012年第4期46卷 272-280页

作者： Consuelos Salas, Laura Robles Cárdenas, Manuel Zhang, Muhong Escuela de Ingeniería y Arquitectura Instituto Tecnológico y de Estudios Superiores de Monterrey Toluca Estado de México 50110 Campus Toluca Eduardo Monroy Cárdenas 2000 Mexico Ira A. Fulton Schools of Engineering Arizona State University Tempe AZ University Drive and Mill Avenue United States

In this work we present a stochastic programming model minimizing costs, to support the decision process of inventory policy which best satisfies the demand for food in shelters when hurricane winds are about to impact a town. In this model we consider perishable products as well as the first in first out (FIFO) system for their consumption. In order to make the model closer to reality ordering cost is time-varying and we add a penalty cost in case the shortage exceeds a known limit for two days in a row. Finally the cost to dispose of expired food is greater than the purchase cost of the product since throwing away food has ethical implications. Starting from a stochastic programming model, we present a procedure to transform it to a deterministic mixed integer programming model (MIP) with non-convex objective function over its entire domain, which closely states the situation in reality. Preliminary computational results and discussion are presented. © 2012 Elsevier Ltd.

关键词： Emergency management Hurricane Inventory policies Mixed integer programming model Perishable products inventory stochastic programming model

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A Monte Carlo Optimization and Dynamic programming Approach for Managing MRI Examinations of Stroke Patients

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2011年第11期56卷 2515-2529页

作者： Geng, Na Xie, Xiaolan Augusto, Vincent Jiang, Zhibin Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China Ecole Natl Super Mines F-42023 St Etienne France

Quick diagnosis is critical to stroke patients, but it relies on expensive and heavily used imaging equipment. This results in long waiting times with potential threats to the patient's life. It is important for neurovascular departments treating stroke patients to reduce waiting times for diagnosis. This paper proposes a reservation process of magnetic resonance imaging (MRI) examinations for stroke patients. The neurovascular department reserves a certain number of appropriately distributed contracted time slots (CTS) to ensure quick diagnosis of stroke patients. Additional MRI time slots can also be reserved by regular reservations (RTS). The problem consists in determining the contract and the control policy to assign patients to either CTS or RTS in order to reach the best compromise between the waiting times and unused CTS. Structural properties of the optimal control policy are proved by an average-cost Markov decision process (MDP) approach. The contract is determined by combining a Monte Carlo approximation approach and local search. Extensive numerical experiments are performed to show the efficiency of the proposed approach and to investigate the impact of different parameters.

关键词： Magnetic resonance imaging (MRI) Markov decision process (MDP) Monte Carlo optimization stochastic programming model stroke patients

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stochastic Vehicle Routing Problem with Uncertain Demand and Travel Time and Simultaneous Pickups and Deliveries

Stochastic Vehicle Routing Problem with Uncertain Demand and...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Lingjuan Hou Hong Zhou School of Economics and Management Beihang University Beijing 100191 P. R. China

ISBN: (纸本)9781424468126;9780769540306

Aiming at the stochastic vehicle routing problems with uncertain demand and travel time and with simultaneous pickups and deliveries, a stochastic programming model is formulated and an improved genetic algorithm is proposed for routes optimization. Self-adaptive mechanism is introduced for amending the fitness value to overcome the premature convergence effectively and to improve the efficiency of the algorithm. The performance of the algorithm is discussed under a variety of problem settings and parameters value by the numerical experiments and sensitivity analysis. Results demonstrate that not only the proposed algorithm obtains even better results, but also it has a good robustness.

关键词： stochastic demand stochastic travel time stochastic programming model genetic algorithm

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Studies of stochastic programming models using possibility and necessity measures for linear programming problems with fuzzy random variable coefficients

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ELECTRONICS AND COMMUNICATIONS IN JAPAN PART III-FUNDAMENTAL ELECTRONIC SCIENCE 2005年第1期88卷 68-75页

作者： Katagiri, H Sakawa, M Ishii, H Hiroshima Univ Grad Sch Engn Higashihiroshima 7398527 Japan Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan

This paper considers the multi-objective linear programming problem and discusses the case in which the coefficients of the objective function are fuzzy random variables. First, the fuzzy goal is introduced into the objective function, considering the fuzzy decision of the human decision-maker. We consider a model in which the possibility or the necessity that the objective function value achieves the fuzzy goal is maximized on the basis of fuzzy programming or possibility programming. It is noted that the possibility or necessity fluctuates stochastically, and a decision-making process based on the stochastic programming model is proposed. After modifying the problem with constraint into an equivalent deterministic problem, the convex programming problem with a parameter is introduced. Then, an algorithm is proposed in which the optimal solution is derived, combining nonlinear programming and the bisection method. (C) 2004 Wiley Periodicals, Inc.

关键词： fuzzy random transform possibility measure necessity measure stochastic programming model convex programming

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Interactive fuzzy random multiobjective programming based on M-α-Pareto optimality and stochastic programming models

Interactive fuzzy random multiobjective programming based on...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Katagiri, H Sakawa, M Kato, K Nishizaki, I Danjyo, H Hiroshima Univ Grad Sch Engn Higashihiroshima 7398527 Japan

ISBN: (纸本)0780392981

This paper deals with multiobjective linear programming problems involving fuzzy random variable coefficients and provides new solution concepts based on M alpha-Pareto optimality and stochastic programming models. Fuzzy goals are introduced to consider the imprecise of the decision maker's judgment for objective functions. After the formulated problem is transformed into the deterministic one, an interactive algorithm based on the reference point method is constructed to solve the deterministic problem.

关键词： fuzzy random variable multiobjective linear programming M-alpha-Pareto optimality stochastic programming model interactive decision making

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WASTE ALLOCATION modelS FOR RISK ASSESSMENT OF WATER-QUALITY MANAGEMENT IN A RIVER BASIN

WASTE ALLOCATION MODELS FOR RISK ASSESSMENT OF WATER-QUALITY...

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15TH BIENNIAL CONF OF THE INTERNATIONAL ASSOC ON WATER POLLUTION RESEARCH AND CONTROL

作者： WEN, CG Taiwan

ISBN: (纸本)0080407749

This paper proposes a stochastic water quality management model which considers river flow as a random variable and optimizes waste allocation at point sources. The model is subjected to a chance constrain which can be converted into an equivalent deterministic constrain, and then can be solved by the use of the available deterministic programming algorithm. The allowable discharge loads and degree of required removal of each point source of a river basin are optimized under various degrees of reliability, and can be employed as information for decision making to decide the most suitable treatment degree of wastewater in a river basin.

关键词： WASTE ALLOCATION modelS RISK ASSESSMENT stochastic programming model UNIFORM TREATMENT ZONE UNIFORM TREATMENT PROBABILISTIC programming RELIABILITY LINEAR programming

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