Simulation-based optimization for a capacitated multi-echelon production-inventory system

Güller, Mustafa; Uygun, Yılmaz; Noche, Bernd

doi:10.1057/jos.2015.5

Cited by 40 publications

(18 citation statements)

References 32 publications

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“…Similarly, [311] compare different algorithms for near-optimal solutions after having encountered difficulties using an exact approach. Meta-heuristics allow to explore the search space more efficiently and effectively, especially if they are tailored to the individual problem [119]. Different meta-heuristic algorithms, such as Evolutionary Computation, Tabu Search, Particle Swarm Optimization (PSO) or Simulated Annealing (SA) have been successfully applied to various logistics optimization problems [253].…”

Section: Meta-heuristicsmentioning

confidence: 99%

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

Heinzl¹

2020

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Production Planning (PPC) optimization in the operation of industrial production plants enables to achieve energy savings and improve energy efficiency. To provide decision support in production planning, simulation-based methods are particularly well-suited for complex production system to assess different planning scenarios and evaluate them with regard to their energy demand. To this end, a hybrid discrete/continuous modeling approach based on the Discrete-Event System Specification (DEVS) is investigated in this thesis. Hybrid modeling allows to accurately capture material flows as discrete entities on one hand and continuous energy flows on the other hand, in the production as well as for other domains, such as heating or cooling, up to the thermal building envelope, including their dynamic interactions. A meta-heuristic optimization procedure for operative production planning evaluates energy efficiency together with other production goals (delivery tardiness, storage costs, etc.) as part of a multi-objective optimization. The procedure follows a hybrid Variable Neighborhood Search (VNS) meta-heuristic and uses the hybrid simulation for the energetic evaluation of production programs. The VNS uses special energy-related operators, for example to optimize the setup times of heating ovens, in order to save energy. Furthermore, to support the modeling process of such DEVS-based simulations in practical applications, a domain-specific model abstraction is designed, which allows to describe hybrid simulation models in an intuitive way. The method is based on a Model-Driven Engineering (MDE) process and defines a component-based meta-model for production systems. Concrete implementations can be derived from the abstract specification by means of model transformations. Proof-of-concept implementations are realized to evaluate the individual contributions and case studies from industry demonstrate the practical applicability. The hybrid simulation approach was implemented in its entirety as a simulator prototype, together with reusable model components, which can be used by practitioners to design new application models with reduced efforts. Altogether, these methods contribute to the integration of energy efficiency aspects into modern PPC systems and to increase energy efficiency in production. i Kurzfassung Im operativen Betrieb von industriellen Anlagen lassen sich durch optimierte Produktionsplanung und-steuerung (PPS) gezielt Energieeinsparungen erreichen und die Energieeffizienz verbessern. Zur Entscheidungsunterstützung bieten sich gerade bei komplexen Produktionssystemen simulationsbasierte Methoden an, die es ermöglichen, unterschiedliche Planungsszenarien zu vergleichen und hinsichtlich ihres Energieeinsatzes zu bewerten. Dafür wird in der vorliegenden Arbeit ein hybrider diskret/kontinuierlicher Modellierungsansatz untersucht, der auf der Discrete-Event System Specification (DEVS) basiert. Die hybride Modellierung erlaubt es einerseits die Materialflüsse als diskrete Entitäten, andererseits auch die zei...

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Section: Meta-heuristicsmentioning

confidence: 99%

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

Heinzl¹

2020

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“…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. In another related paper, Wang et al [111] employed simulation in a transportation study to estimate the cost and reliability of solutions in a routing problem.…”

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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“…Compared with the results of non-dominated sequencing genetic algorithm, it shows that the proposed method can effectively solve the optimal replenishment problem in supply chain environment. Güller et al [16] studied a multi-echelon production-inventory system under a stochastic environment and used simulation-based optimization approach to determine the optimal inventory control parameters. He et al [17] proposed a novel simulation-based heuristic method to solving the modeling and optimization problem of multi-echelon contain in supply chain network, where the objective is subject to the minimization of the total supply chain service cost.…”

Section: Introductionmentioning

confidence: 99%

Simulation-based optimization of control policy on multi-echelon inventory system for fresh agricultural products

Feng

Chen

et al. 2019

International Journal of Agricultural and Biological Engineering

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As fresh agricultural products are perishable and vulnerable, reducing inventory cost is a strategic target for supply chain enterprises. How to design a reliable multi-echelon inventory control policy is still a great challenge. Therefore, the inventory cost of a three-level fresh agricultural products inventory system was firstly mathematically analyzed. Then, the simulation-based optimization model of the multi-echelon inventory system for fresh agricultural products was proposed by using the Flexsim simulation software and the improved particle swarm optimization algorithm. Finally, the multi-echelon inventory system is simulated based on a large number of survey data. Simulation results demonstrate that the proposed simulation-based optimization model of multi-echelon inventory system for fresh agricultural products can provide decision-making and technical support for the formulation of inventory control policy, and also it shows that the modeling of system simulation is an effective method to solve the problem of complex system.

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Simulation-based optimization for a capacitated multi-echelon production-inventory system

Cited by 40 publications

References 32 publications

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

Methods for Hybrid Modeling and Simulation-Based Optimization in Energy-Aware Production Planning

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

Simulation-based optimization of control policy on multi-echelon inventory system for fresh agricultural products

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