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نتیجه جستجو - Simulation optimization

تعداد مقالات یافته شده: 3
ردیف عنوان نوع
1 An efficient simulation optimization methodology to solve a multi-objective problem in unreliable unbalanced production lines
یک روش بهینه سازی شبیه سازی کارآمد برای حل یک مشکل چند هدف در خطوط تولید نامتوازن غیرقابل اعتماد-2019
This research develops an expert system to addresses a novel problem in the literature of buffer allo- cation and production lines. We investigate real-world unreliable unbalanced production lines where all time-based parameters are probabilistic including time between parts arrivals, processing times, time be- tween failures, repairing times, and setup times. The main contributions of the paper are a twofold. First and foremost, the mean processing times of workstations and buffer capacities, unlike the existing litera- ture, are considered as decision variables in a multi-objective optimization problem which maximizes the throughput rate and minimizes the total buffer capacities as well as the total cost of the mean process time reductions. Secondly, an efficient methodology is developed that can precisely reflect a real-world system without any unrealistic and/or restrictive assumptions on the probabilistic nature of the system, which are commonly assumed in the existing literature. One of the greatest challenges in this research is to estimate the throughput rate function since it highly depends on the random behavior of the sys- tem. Thus, a simulation optimization approach is developed based on the Design of Experiments and Re- sponse Surface Methodology to fit a regression model for throughput rate. Finally, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Non-dominated Ranked Genetic Algorithm (NRGA) are used to gener- ate high-quality solutions for the aforementioned problem. This methodology is run on a real numerical case. The experimental results confirm the advantages of the proposed methodology. This methodology is an innovative expert system with a knowledge-base developed through this simulation optimization approach. This expert system can be applied to complex production line problems in large or small scale with different types of decision variables and objective functions. The application of this expert system is transformative to other manufacturing systems.
Keywords: Unreliable unbalanced production lines | Buffer allocation problem | Simulation optimization | Design of experiments | Response surface methodology | Meta-heuristics
مقاله انگلیسی
2 Simulation-based multi-objective model for supply chains with disruptions in transportation
شبیه سازی مبتنی بر مدل چند هدفه برای زنجیره تامین با اختلال در حمل و نقل-2017
Unpredictable disruptions (e.g., accidents, traffic conditions, among others) in supply chains (SCs) mo tivate the development of decision tools that allow designing resilient routing strategies. The transpor tation 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 fra mework is effective and overcomes the limitations of the multi-objective stochastic minimum cost flow problem (which becomes intractable for large-scale instances).
Keywords: Minimum cost flow | Simulated annealing | Simulation optimization | Stochastic multi-objective optimization | Resilient supply chains
مقاله انگلیسی
3 Event driven strategy based complete rescheduling approaches for dynamic m identical parallel machines scheduling problem with a common server
رویکردهای زمانبندی مجدد کامل مبتنی بر استراتژی رویداد محور برای مساله زمانبندی ماشین های موازی پویا با شناسه m با یک سرور مشترک-2016
This paper addresses the dynamic m identical parallel machine scheduling problem in which the sequence dependent setup operations between the jobs are performed by a single server. An event driven rescheduling strategy based simulation optimization model is proposed by inspiration from limited order release procedure (Bergamaschi, Cigolini, Perona, & Portioli, 1997) for being able to tackle the changing environment of the system. The proposed event driven rescheduling strategy is based on the logic of controlling the level of the physical work-in-process on the shop floor. A simulated annealing and dispatching rules based complete rescheduling approaches as the simulation based optimization tools are proposed and adapted to the developed simulation model for generating new schedules depending on the proposed event driven rescheduling strategy. The objective of this study is to minimize the length of schedule (makespan). The performances of the approaches are compared on a hypothetical simulation case. The results of the extensive simulation study indicate that simulated annealing based complete rescheduling approach produces better scheduling performance.© 2015 Elsevier Ltd. All rights reserved.
Keywords: Dynamic scheduling | m identical parallel machines scheduling with a common server | Simulation | Simulated annealing | Dispatching rules | Sequence dependent setup times
مقاله انگلیسی
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