Simulation-based multi-objective model for supply chains with disruptions in transportation

被引：15

作者：

Chavez, Hernan ^{[1
]}

Castillo-Villar, Krystel K. ^{[1
]}

Herrera, Luis ^{[2
]}

Bustos, Agustin ^{[3
]}

机构：

[1] Univ Texas San Antonio, Dept Mech Engn, San Antonio, TX 78249 USA

[2] Tecnol Monterrey, Dept Ind & Syst Engn, Mexico City 01389, DF, Mexico

[3] Inst Mexicano Transporte, Integrated Transport Res Ctr, Sanfandila 76700, Queretaro, Mexico

来源：

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING | 2017年 / 43卷

基金：

美国食品与农业研究所;

关键词：

Minimum cost flow; Simulated annealing; Simulation optimization; Stochastic multi-objective optimization; Resilient supply chains; COST FLOW PROBLEM; OPTIMIZATION; ALGORITHM; NETWORKS;

D O I：

10.1016/j.rcim.2015.12.008

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Unpredictable disruptions (e.g., accidents, traffic conditions, among others) in supply chains (SCs) motivate the development of decision tools that allow designing resilient routing strategies. The transportation problem, for which a model is proposed in this paper, consists of minimizing the stochastic transportation time and the deterministic freight rate. This paper extends a stochastic multi-objective minimum cost flow (SMMCF) model by proposing a novel simulation-based multi-objective optimization (SimMOpt) solution procedure. A real case study, consisting of the road transportation of perishable agricultural products from Mexico to the United States, is presented and solved using the proposed SMMCF-Continuous/SimMOpt solution framework. In this case study, time variability is caused by the inspection of products at the U.S.-Mexico border ports of entry. The results demonstrate that this framework is effective and overcomes the limitations of the multi-objective stochastic minimum cost flow problem (which becomes intractable for large-scale instances). (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：39 / 49

页数：11

共 32 条

[1]

Ackley D. H., 1987, GENETIC ALGORITHMS S, V1, P170

[2]

[Anonymous], 2009, METAHEURISTICS DESIG

[3]

[Anonymous], 2005, MULTICRITERIA OPTIMI

[4]

[Anonymous], J APPL MATH

[5] Efficient Frontier for Multi-Objective Stochastic Transportation Networks in International Market of Perishable Goods [J].

Bustos, A. ;

Herrera, L. ;

Jimenez, E. .

JOURNAL OF APPLIED RESEARCH AND TECHNOLOGY, 2014, 12 (04) :654-665

[6] Simulation optimization: Methods and applications [J].

Carson, Y ;

Maria, A .

PROCEEDINGS OF THE 1997 WINTER SIMULATION CONFERENCE, 1997, :118-126

[7]

Chavez H, 2014, 2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN PRODUCTION AND LOGISTICS SYSTEMS (CIPLS), P98, DOI 10.1109/CIPLS.2014.7007167

[8]

del Castillo G., 2007, Estudio de Puertos de Entrada Mexico-Estados Unidos: Analisis de capacidades y recomendaciones para incrementar su eficiencia. Capacities from United States Mexico Border ports and recommendations to increase their efficiency

[9] Finding non-dominated solutions in bi-objective integer network flow problems [J].

Eusebio, Augusto ;

Figueira, Jose Rui .

COMPUTERS & OPERATIONS RESEARCH, 2009, 36 (09) :2554-2564

[10] Solving scalarized multi-objective network flow problems using an interior point method [J].

Fonseca, Margarida ;

Figueira, Jose Rui ;

Resende, Mauricio G. C. .

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 2010, 17 (05) :607-636

← 1 2 3 4 →