Hybrid simulation based optimization approach for supply chain management

Nikolopoulou, Amalia; Ierapetritou, Marianthi G.

doi:10.1016/j.compchemeng.2012.06.045

Cited by 77 publications

(36 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This approach can be implemented in various ways, depending on the simulation paradigms chosen. Examples can be found in Nikolopoulou and Ierapetritou [38], Santoso et al [39] and Almeder et al [40] for agent-based simulation, Monte Carlo simulation and DES, respectively. In the blood supply chain, optimization models have been used less frequently than in industrial supply chains.…”

Section: Methodsmentioning

confidence: 99%

Simulation-optimization model for production planning in the blood supply chain

Osorio

Brailsford

Smith

et al. 2016

Health Care Manag Sci

View full text Add to dashboard Cite

Production planning in the blood supply chain is a challenging task. Many complex factors such as uncertain supply and demand, blood group proportions, shelf life constraints and different collection and production methods have to be taken into account, and thus advanced methodologies are required for decision making. This paper presents an integrated simulation-optimization model to support both strategic and operational decisions in production planning. Discrete-event simulation is used to represent the flows through the supply chain, incorporating collection, production, storing and distribution. On the other hand, an integer linear optimization model running over a rolling planning horizon is used to support daily decisions, such as the required number of donors, collection methods and production planning. This approach is evaluated using real data from a blood center in Colombia. The results show that, using the proposed model, key indicators such as shortages, outdated units, donors required and cost are improved.

show abstract

Section: Methodsmentioning

confidence: 99%

Simulation-optimization model for production planning in the blood supply chain

Osorio

Brailsford

Smith

et al. 2016

Health Care Manag Sci

View full text Add to dashboard Cite

show abstract

“…Table 12 demonstrates the number of S-O frameworks of each type in the context of SC. Except the frameworks developed by Nikolopoulou et al [106], Chen et al [107] and Almeder et al [108], where a combination of the mentioned S-O frameworks has been employed, each distinct group of S-O studies is discussed separately in the upcoming subsections. In order to assist the researchers and students in the field to trace this emerging topic, the top research areas in the field of S-O frameworks (not limited to the context of SC), as well as information on the top contributing research organizations are summarized in Tables 13 and 14.…”

Section: Simulation-optimizationmentioning

confidence: 99%

“…The same recursive framework is applied for the re-configuration of an express delivery logistic network and logistics in a multi-echelon SC in studies by Kim et al [137] and Hochmuth et al [138], respectively. In some other studies of this type, the design of SCN is done through the optimization of decision variables from different SCM elements [106][107][108].…”

Section: Optimization-based Simulationmentioning

confidence: 99%

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Pourhejazy

Kwon

2016

Sustainability

View full text Add to dashboard Cite

Abstract:The possibilities of applying Operations Research (O.R.) techniques in the design of real-world systems are vast. The optimization and design of the supply chain network (SCN) is one of the relevant topics that has directed the attention of many scholars. Sound decisions in this regard, including the proper selection of the facility's location, transportation modes and routes and inventory management policies, can noticeably improve the systems performance. Over 380 articles published between 2005 and 2016 in the ISI/Web of Science database have applied advanced O.R. techniques in SCN optimization studies. This paper offers a systematic review of these published contributions by focusing on two categories of O.R. approaches most recently applied for the design of SC systems: integrated mathematical modeling and simulation-optimization (S-O) frameworks. A taxonomy analysis of the mentioned approaches is presented based on the supply chain elements. A bibliometric analysis is also conducted to provide technical insights into the possible gaps in the field. Moreover, the relevant studies on SC sustainability are highlighted. The research results are supportive of the S-O frameworks as either an alternative approach or an effective solution method for the integrated problems. The research outcomes can provide researchers in the field with useful details of the integrated problems and S-O frameworks as the most recent O.R. methodologies in the field of SC optimization.

show abstract

“…An extensive literature is available for combination of optimization and simulation in hybrid approaches in Supply Chain Management (SCM) context (see e.g., Almeder et al 2009;Acar et al 2010;Nikolopoulou and Ierapetritou 2012;Sahay and Ierapetritou 2013), especially for production and distribution (see e.g., Bilgen and Ç elebi 2013;Sel and Bilgen 2014;Safaei et al 2010), location decisions, and perishable goods (see e.g., Keizer et al 2015). However, the application to transportation area is limited.…”

Section: Introductionmentioning

confidence: 99%

Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty

et al. 2016

View full text Add to dashboard Cite

The increasing volumes of road transportation contribute to congestion on road, which leads to delays and other negative impacts on the reliability of transportation. Moreover, transportation is one of the main contributors to the growth of carbon dioxide equivalent emissions, where the impact of road transportation is significant. Therefore, governmental organizations and private commercial companies are looking for greener transportation solutions to eliminate the negative externalities of road transportation. In this paper, we present a novel solution framework to support the operational-level decisions for intermodal transportation networks using a combination of an optimization model and simulation. The simulation model includes stochastic elements in form of uncertain travel times, whereas the optimization model represents a deterministic and linear multi-commodity service network design formulation. The intermodal transportation plan can be optimized according to different objectives, including costs, time and CO 2 e emissions. The proposed approach is successfully implemented to real-life scenarios where differences in transportation plans for alternative objectives are presented. DOI 10.1007/s10696-016-9267-1 show that the approach is capable of delivering reliable solutions and identifying possible disruptions and alternatives for adapting the unreliable transportation plans.

show abstract

Hybrid simulation based optimization approach for supply chain management

Cited by 77 publications

References 26 publications

Simulation-optimization model for production planning in the blood supply chain

Simulation-optimization model for production planning in the blood supply chain

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Hybrid simulation and optimization approach for green intermodal transportation problem with travel time uncertainty

Contact Info

Product

Resources

About