Simulation-based optimization framework for multi-echelon inventory systems under uncertainty

Chu, Ying‐Hao; You, Fengqi; Wassick, John M.; Agarwal, Anshul

doi:10.1016/j.compchemeng.2014.10.008

Cited by 69 publications

(51 citation statements)

References 52 publications

(52 reference statements)

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“…The approach is adopted in several works in order to reduce the complexity of the management of the supply chain and to assess its performance [8]. The models based on communicating agent for the simulation of SC are in vogue, filling thereby the gaps of analytical models to model the chain with all its complexity [9][10].…”

Section: The Modeling and The Simulation Of The Connectivitymentioning

confidence: 99%

“…Thus, developing a process of negotiation between functional agents. Other work as [15] designs an Information System for the Multimodal Management on the basis of MA, to that is added the thesis of [16] which employment the DAI for the modeling of Meta heuristic, and [17] which he combines the mathematical optimization and the DAI modeling for the development of its system.…”

Section: The Modeling and The Simulation Of The Connectivitymentioning

confidence: 99%

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The elaboration of a manufacturing flow connectivity model, based on Multi Agent System

et al. 2017

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Abstract. Nowadays, manufacturing industries are operating in a highly complex and unforeseeable economic context. Therefore, they tend, by necessity toward short term inter-firms coordination. Thus, found increasingly located at the intersection of corporate networks, to overcome their inability to quickly meet the needs of clients, facing thereby several complications related to the coordination between heterogeneous entities. Managing the flow of a network, made up of different links became a major challenge. The appeals to decision support tools and simulation are wished all the more to correlate the dynamics of the system and the targeted objectives, to assess the configurations effectiveness. Thus, enhance their performance.The aim of this paper was to establish a model of the industrial flow connectivity; Afterward, we've detailed a network configuration model based on the multi-agents systems, to study the interactions between all the actors and give a more realistic vision onto manufacturing coordination in the supply chain.

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Section: The Modeling and The Simulation Of The Connectivitymentioning

confidence: 99%

Section: The Modeling and The Simulation Of The Connectivitymentioning

confidence: 99%

The elaboration of a manufacturing flow connectivity model, based on Multi Agent System

et al. 2017

View full text Add to dashboard Cite

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“…The assessment of different solutions from the Pareto optimal set using simulation is another novel idea tested by Napalkova et al [115]. Other papers gained the advantage of evaluating the optimal solutions in terms of the other measures, such as KPIs in sourcing by Ding et al [116], and the qualitative measures, such as customer satisfaction in the design of inventory systems by Chu et al [117]. In one recent relevant study, M. Gueller et al [118] applied a multi-objective particle swarm optimization algorithm for the optimization of inventory decision variables (reorder point and order quantity), to be evaluated in an object-oriented simulator in terms of different performance measures such as customer service level and demand fulfillment rate, among others.…”

Section: Simulation-based Optimizationmentioning

confidence: 99%

“…In another possible approach, the given social and environmental restrictions can be fulfilled in the simulation part of S-O frameworks, while the cost criterion can be optimized through an external optimizer. Other studies have optimized the customer service level in addition to the variable costs [115,117,118,126,130]. In a simulation optimization framework developed by [143], the fitness function is calculated using a lexicographic structure where the individual optimum solutions are ranked based on total cost, customer service level and the average work in progress material.…”

Section: Studies On Sustainabilitymentioning

confidence: 99%

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

Pourhejazy

Kwon

2016

Sustainability

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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.

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“…In this article, we mainly want to show differences of results gained through solving optimization task using SPEA2 and performance for two control inventory systems and different shipping delays. The objective of inventory optimization is to maintain optimal inventory levels depending on demand and to minimize inventory holding cost while avoiding shortages [30]. In [31] Pareto-based meta-heuristic algorithm are used to solve the bi-objective inventory models.…”

Section: Introductionmentioning

confidence: 99%

Comparison of a Perpetual and PD Inventory Control System with Smith Predictor and Different Shipping Delays Using Bicriterial Optimization and SPEA2

Chołodowicz

Orłowski

2016

PAR

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Inventory optimization is critical in inventory control systems. The complexity of real-world inventory systems results in a challenging optimization problem, too complicated to solve by conventional mathematical programing methods. The aim of this work is to confront: a perpetual inventory system found in the literature and inventory system with PD control and Smith predictor proposed by the authors. To be precise, the two control systems for inventory management are analyzed with different shipping delays and compared. With regard to complexity of the proposed control system, we use a SPEA2 algorithm to solve optimization task for assumed scenario of the market demand. The objective is to minimize the inventory holding cost while avoiding shortages. A discrete-time, dynamic model of inventory system is assumed for the analysis. In order to compare the results of systems, Pareto fronts and signal responses are generated.

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Simulation-based optimization framework for multi-echelon inventory systems under uncertainty

Cited by 69 publications

References 52 publications

The elaboration of a manufacturing flow connectivity model, based on Multi Agent System

The elaboration of a manufacturing flow connectivity model, based on Multi Agent System

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

Comparison of a Perpetual and PD Inventory Control System with Smith Predictor and Different Shipping Delays Using Bicriterial Optimization and SPEA2

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