scholarly journals Optimization of Ordering and Allocation Scheme for Distributed Material Warehouse Based on IGA-SA Algorithm

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1746
Author(s):  
Han Jiang ◽  
Yunlong Wu ◽  
Qing Zhang
Keyword(s):  
Simulated Annealing Algorithm ◽  
Cost Model ◽  
Allocation Scheme ◽  
Improved Genetic Algorithm ◽  
Inventory Cost ◽  
Safety Stock ◽  
Modern Enterprise ◽  
Annealing Algorithm ◽  
The Cost ◽  
Optimal Ordering

The distributed material warehouse is the crucial link in the process of modern enterprise construction, and the goal of the enterprise is to save the cost of material distribution and reduce the time of distribution. In order to obtain the optimal ordering and allocation scheme, firstly, a distributed inventory system consisting of an ordering centre, a material coordination centre and n material warehouses are considered, and the cost model of ordering and allocation of the distributed material warehouse is established. Next, the safety stock and the ordering point of the distributed material warehouse are solved. Then the improved genetic algorithm-simulated annealing algorithm (IGA-SA) is used to solve the optimization of the distributed material warehouse. Finally, the application example is given. The results show that the IGA-SA algorithm can effectively reduce inventory cost and improve inventory utilization.

Review on Inventory Controlling of Building Materials Supply Chain from Uncertainty Demands in Civil Engineering

2012 ◽  
Vol 174-177 ◽  
pp. 3441-3443
Author(s):  
Bin Yang
Keyword(s):  
Supply Chain ◽  
Building Materials ◽  
Simulated Annealing Algorithm ◽  
Supply And Demand ◽  
Cost Models ◽  
Inventory Cost ◽  
Inventory Costs ◽  
Total Inventory ◽  
Annealing Algorithm ◽  
The Difference

Inventory control is a necessary strategy that enterprises use to offset the effect of uncertainties in manufacturing, supply and demand. Normally, probability distribution is used to analyze the uncertainty problems, however, this analysis can’t be completed with inadequate data, resulting in an increase in inventory costs. The paper establishes inventory cost models of single supply chain member under uncertainty demands and applies Simulated Annealing Algorithm to imitate the models in 52 weeks to seek for the optimal speaking for amount and anew speaking for point so that compares the difference of supply chain total inventory cost and the sufficing rate of order for goods between independently and collaborated controlling strategy in supply chain, and in order to provide the necessary theoretical supports for the enterprises to establish supply chain partnerships and possibly improve the supply chain capability of providing external integration.

scholarly journals Research on airport multi-objective optimization of stand allocation based on simulated annealing algorithm

2021 ◽  
Vol 18 (6) ◽  
pp. 8314-8330
Author(s):  
Ningning Zhao ◽  
◽  
Mingming Duan
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Objective Function ◽  
Simulated Annealing Algorithm ◽  
Allocation Scheme ◽  
Multi Objective Optimization ◽  
Practical Application ◽  
Allocation Decision ◽  
Multi Objective ◽  
Annealing Algorithm

<abstract> <p>In this study, a multi-objective optimized mathematical model of stand pre-allocation is constructed with the shortest travel distance for passengers, the lowest cost for airlines and the efficiency of stand usage as the overall objectives. The actual data of 12 flights at Lanzhou Zhongchuan Airport are analyzed by application and solved by simulated annealing algorithm. The results of the study show that the total objective function of the constructed model allocation scheme is reduced by 40.67% compared with the actual allocation scheme of the airport, and the distance traveled by passengers is reduced by a total of 4512 steps, while one stand is saved and the efficiency of stand use is increased by 31%, in addition to the reduction of airline cost by 300 RMB. In summary, the model constructed in the study has a high practical application value and is expected to be used for airport stand pre-allocation decision in the future.</p> </abstract>

scholarly journals Optimization and Design of Hammerheads and Fenders on Scrap Metal Shredders Based on Improved Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
He Tian ◽  
Guoqiang Wang ◽  
Kangkang Sun ◽  
Zeren Chen ◽  
Chuliang Yan ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Dynamic Balance ◽  
Optimal Solution ◽  
Scrap Metal ◽  
Improved Genetic Algorithm ◽  
Multiple Traveling Salesman Problem ◽  
Local Optimal Solution ◽  
Annealing Algorithm

Dynamic unbalance force is an important factor affecting the service life of scrap metal shredders (SMSs) as the product of mass error. Due to the complexity of hammerheads arrangement, it is difficult to take all the parts of the hammerhead into account in the traditional methods. A novel optimization algorithm combining genetic algorithm and simulated annealing algorithm is proposed to improve the dynamic balance of scrap metal shredders. The optimization of hammerheads and fenders on SMS in this paper is considered as a multiple traveling salesman problem (MTSP), which is a kind of NP-hard problem. To solve this problem, an improved genetic algorithm (IGA) combined with the global optimization characteristics of genetic algorithm (GA) and the local optimal solution of simulated annealing algorithm (SA) is proposed in this paper, which adopts SA in the process of selecting subpopulations. The optimization results show that the resultant force of the shredder central shaft by using IGA is less than the traditional metaheuristic algorithm, which greatly improves the dynamic balance of the SMS. Validated via ADAMS simulation, the results are in good agreement with the theoretical optimization analysis.

scholarly journals ANALISIS BIAYA PERSEDIAAN BAHAN BAKU IKAN DAN PERHITUNGAN ECONOMIC ORDER QUANTITY (EOQ) PADA RUMAH MAKAN IKAN BAKAR KINAMANG

2018 ◽  
Vol 13 (02) ◽  
Author(s):  
Melinda Miranda Wijaya ◽  
David P. E. Saerang ◽  
Meily Y. B. Kalalo
Keyword(s):  
Raw Materials ◽  
Raw Material ◽  
Economic Order Quantity ◽  
Economic Order ◽  
Order Quantity ◽  
Inventory Cost ◽  
Safety Stock ◽  
Purchase Order ◽  
Reorder Point ◽  
The Cost

            The cost of raw material inventory is a sacrifice of economic resources, measured in units of money, which have occurred or are likely to occur for raw material inventory, consisting of purchase costs, storage costs, and inventory shortage. This study aims to determine (1) Total Inventory Cost (TIC) based on RM policy. Kinamang Fuel Fish and Economic Order Quantity (EOQ) method during 2017 (2) Frequency of ordering of efficient fish raw material during 2017 (3) Quantity of safety stock and when to reorder point of raw materials fish in RM. Ikan Bakar Kinamang during 2017. This research is a descriptive research with qualitative approach. And use case study method. The result of the research shows that the Cost of Fish Raw Material Supplies at Kinamang Fuel Fish Restaurant is still not economical because the purchase (order) is only based on the previous sales estimate, and does not take into account economically the expenses incurred for the purchase and storage of fish raw materials the. Precisely with the calculation of Economic Order Quantity (EOQ), the cost of raw materials inventory of fish is much less, and can determine properly and correctly about the safety stock (safety stock), and reorder (reorder point).Keywords: Inventory Cost, EOQ, Frequency, Safety Stock, ROP

scholarly journals ANALISIS KEBIJAKAN INVENTORI PADA KOMPONEN DARAH PACKED RED CELL (PRC)

2019 ◽  
Vol 3 (2) ◽  
pp. 94-105
Author(s):  
Muchammad Fauzi (Universitas Widyatama - Indonesia) ◽  
Senator Nur Bahagia (Institut Teknologi Bandung - Indonesia)
Keyword(s):  
Total Population ◽  
Cost Savings ◽  
Red Cell ◽  
Who Guidelines ◽  
Inventory Cost ◽  
Safety Stock ◽  
Optimal Value ◽  
Total Inventory ◽  
The Cost ◽  
The City

Abstract By following WHO guidelines, the minimum blood availability is 2% of the population. The total population of Indonesia in 2016 is 261.115.456, so ideally it takes 5.222.309 blood bags. In 2013-2015 for 36 months, there were 26 overstock events and 10 stockout events. The data shows that the frequency of over-supply is more frequent than over-demand. The high overstock has an impact on the high costs incurred by the City of Bandung PMI, if there is overstock there are two costs to be incurred, namely the cost of storing if the blood is still in good use and the cost of overstock if the blood is more than the expiration date. The purpose of this study was to determine the optimal value of inventory levels to reduce wastage of blood culling due to overstock occurring at PMI Bandung. The research method uses a quantitative approach to the optimization model of inventory policy, namely Uncertainty EOQ. The optimal amount of supplies that must be provided is at intervals of 8,705 - 9,375 blood bags with a large safety stock 403 blood bags and the ordering point is at the level of supplies of 5.706 blood bags. This proposal can provide a total inventory cost savings of Rp6.622.659.034/year. Keywords: Blood, Overstock, EOQ, Uncertainty Abstrak Sesuai dengan panduan WHO, ketersediaan darah minimal adalah 2% dari jumlah penduduk. Jumlah penduduk Indonesia tahun 2016 adalah 261.115.456 jiwa, maka idealnya dibutuhkan 5.222.309 kantong darah. Tahun 2013-2015 selama 36 bulan, terdapat 26 kejadian overstock dan 10 kejadian stoc-kout. Data tersebut menunjukan bahwa frekuensi over-supply lebih sering dibandingkan over-demand. Tingginya overstock berdampak pada tingginya biaya yang dikeluarkan oleh PMI Kota Bandung, jika terjadi overstock ada dua biaya yang harus dikeluarkan, yaitu biaya simpan jika darah masih dalam masa baik digunakan dan biaya overstock jika darah sudah lebih dari tanggal kadaluarsa. Tujuan penelitian ini adalah mengetahui nilai tingkat persediaan yang optimal untuk mengurangi pemborosan pemusnahan darah akibat overstock yang terjadi di PMI Kota Bandung. Metode penelitian menggunakan pendekatan kuantitatif model optimasi pada kebijakan inventori yaitu EOQ Tak Tentu Berisiko Terkendali. Jumlah persediaan optimal yang harus disediakan berada di interval 8.705 – 9.375 kantong darah dengan besar safety stock 403 kantong darah dan titik pemesanan berada di tingkat persediaan 5.706 kantong darah. Usulan ini dapat memberikan penghematan total biaya persediaan sebesar Rp6.622.659.034/tahun. Kata kunci: Darah, Overstock, EOQ, Tak Tentu

Research on Optimal Deployment of HWSN Node Cost Based on Simulated Annealing Algorithm

2014 ◽  
Vol 651-653 ◽  
pp. 1921-1924
Author(s):  
Ji Tao Shen ◽  
Jun Yang Zhang
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Fault Tolerant ◽  
Monitoring Network ◽  
Optimization Method ◽  
Perception Model ◽  
Annealing Algorithm ◽  
Target Monitoring ◽  
The Cost ◽  
Network Fault Tolerance

An optimal heterogeneous sensor differentiated deployment schemes based on simulated annealing algorithm is proposed to solve the problems of the high density of distributing heterogeneity nodes in WSN and geographical irregularity of the sensed event. This method can not only apply to Boolean perception model of the node, but also apply to perception model. The algorithm uses the cost of sensors deployment as objective function in the context of assuring the coverage and fault tolerant of networks. The simulation results show that, the optimization method proposed in this paper can effectively convergence, under the premise to ensure network fault tolerance and robustness, reduces the cost of network deployment, improve the quality of target monitoring network.

scholarly journals An Effective Heuristic-Based Approach for Partitioning

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Xibin Zhao ◽  
Hehua Zhang ◽  
Yu Jiang ◽  
Songzheng Song ◽  
Xun Jiao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Simulated Annealing ◽  
Embedded System ◽  
Simulated Annealing Algorithm ◽  
Optimal Solution ◽  
Local Optimal Solution ◽  
Annealing Algorithm ◽  
The Cost ◽  
Combined Algorithm ◽  
Search Capability

As being one of the most crucial steps in the design of embedded systems, hardware/software partitioning has received more concern than ever. The performance of a system design will strongly depend on the efficiency of the partitioning. In this paper, we construct a communication graph for embedded system and describe the delay-related constraints and the cost-related objective based on the graph structure. Then, we propose a heuristic based on genetic algorithm and simulated annealing to solve the problem near optimally. We note that the genetic algorithm has a strong global search capability, while the simulated annealing algorithm will fail in a local optimal solution easily. Hence, we can incorporate simulated annealing algorithm in genetic algorithm. The combined algorithm will provide more accurate near-optimal solution with faster speed. Experiment results show that the proposed algorithm produce more accurate partitions than the original genetic algorithm.

Research on Non-Linear Power Coal Blending Model and its Algorithm

2013 ◽  
Vol 787 ◽  
pp. 71-74
Author(s):  
Ai Chun Ma ◽  
Jie Yang ◽  
Dong Nan Chen ◽  
Jian Ping Ou
Keyword(s):  
Simulated Annealing Algorithm ◽  
Computing Time ◽  
General Regression Neural Network ◽  
Blended Coal ◽  
Ga Algorithm ◽  
Coal Blending ◽  
Non Linear ◽  
Annealing Algorithm ◽  
The Cost ◽  
General Regression

Based on the common used coals and designed coal in a power plant in Hunan, a non-linear coal blending model was built. Exhaust algorithm, genetic algorithm and simulated annealing algorithm were used to solve the model respectively using the lowest cost of the blended coal as the objective function. Three kinds of single coals were blended together according to certain proportions based on 15 kinds of common used single coals. The coal characteristics of blended coals were predicted by the model of General Regression Neural Network. The cost, fitness and predicting time obtained by three different algorithms were compared and analyzed. The results show that the solution is ideal in cost and fitness with exhaust algorithm while the predicting time is very long. GA algorithm is good in cost, computing time and reliability.

scholarly journals A Simulated Annealing Algorithm for Solving Two-Echelon Vehicle Routing Problem with Locker Facilities

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 218
Author(s):  
A. A. N. Perwira Redi ◽  
Parida Jewpanya ◽  
Adji Candra Kurniawan ◽  
Satria Fadil Persada ◽  
Reny Nadlifatin ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Simulated Annealing Algorithm ◽  
Two Phase ◽  
Routing Problem ◽  
Intermediate Facilities ◽  
Annealing Algorithm ◽  
Phase Optimization ◽  
The Cost

We consider the problem of utilizing the parcel locker network for the logistics solution in the metropolitan area. Two-echelon distribution systems are attractive from an economic standpoint, whereas the product from the depot can be distributed from or to intermediate facilities. In this case, the intermediate facilities are considered as locker facilities present in an accessible location in the vicinity of the final customers. In addition, the utilization of locker facilities can reduce the cost caused by the unattended deliveries. The problem is addressed as an optimization model that formulated into an integer linear programming model denoted as the two-echelon vehicle routing problem with locker facilities (2EVRP-LF). The objective is to minimize the cost of transportation with regards to the vehicle travelling cost, the intermediate facilities renting cost, and the additional cost to compensate the customer that needs to travel to access the intermediate facilities. Because of its complexity, a simulated annealing algorithm is proposed to solve the problem. On the other hand, the modelling approach can be conducted by generating two-phase optimization model approaches, which are the p-median problem and the capacitated vehicle routing problem. The results from both methods are compared in numerical experiments. The results show the effectiveness of 2EVRP-LF compared to the two-phase optimization. Furthermore, the simulated annealing algorithm showed an effective performance in solving 2EVRP-LF.

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