A Queuing Model for an Inventory Problem

1957 ◽  
Vol 5 (5) ◽  
pp. 693-703 ◽  
Author(s):  
William Karush
Author(s):  
N. Thirupathi Rao ◽  
Debnath Bhattacharyya ◽  
S. Naga Mallik Raj

2017 ◽  
Vol 1 (2) ◽  
pp. 75
Author(s):  
Budi Setiawan ◽  
Hermanto Hermanto

The Embung Bengawan Project in Tarakan City has several jobs requiring heavy equipment including mechanical soil removal activities. Activity of mechanical soil movement is a series in work of loading and transportation equipment. In order to achieve optimal mechanical soil removal targets, it is necessary to know the performance of the machine during the mechanical soil removal process. The optimization of production is the way to obtain production that is in accordance with optimal conditions of mechanical devices. This paper discusses the optimization of dump truck queue time and the number of dump trucks. Performance calculation tool using the method of production capacity of the tool, and calculate the optimal queue using the Queue Model method. Calculation using queuing model method obtained by result of time required by 3 excavator unit and with combined amount of dump truck will give result of cost equal to Rp 48,097,711 / day, and dump truck waiting time in queue to 1 minute. Then the optimal time is obtained by operating 3 units of excavators with a cost difference of Rp 3,572,826 / day from the real condition of the field that operates 2 excavator units


1973 ◽  
Vol 4 (3) ◽  
pp. 15-20
Author(s):  
Robert C. Shook ◽  
Harold Joseph Highland
Keyword(s):  

Author(s):  
Xiaokun Wang ◽  
Dong Ni

To scientifically and reasonably evaluate and pre-warn the congestion degree of subway transfer hub, and effectively know the risk of subway passengers before the congestion time coming. We analyzed the passenger flow characteristics of various service facilities in the hub. The congested area of the subway passenger flow interchange hub is divided into queuing area and distribution area. The queuing area congestion evaluation model selects M/M/C and M/G/C based on queuing theory. The queuing model and the congestion evaluation model of the distribution area select the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. Queue length and waiting time are selected as the evaluation indicators of congestion in the queuing area, and passenger flow, passenger flow density and walking speed are selected as the evaluation indicators of congestion in the distribution area. And then, K-means cluster analysis method is used to analyze the sample data, and based on the selected evaluation indicators and the evaluation model establishes the queuing model of the queuing area and the TOPSIS model of the collection and distribution area. The standard value of the congestion level of various service facilities and the congestion level value of each service facility obtained from the evaluation are used as input to comprehensively evaluate the overall congestion degree of the subway interchange hub. Finally we take the Xi’an Road subway interchange hub in Dalian as empirical research, the data needed for congestion evaluation was obtained through field observations and questionnaires, and the congestion degree of the queue area and the distribution area at different times of the workday was evaluated, and the congestion of each service facility was evaluated. The grade value is used as input, and the TOPSIS method is used to evaluate the degree of congestion in the subway interchange hub, which is consistent with the results of passenger congestion in the questionnaire, which verifies the feasibility of the evaluation model and method.


2018 ◽  
Vol 2018 ◽  
pp. 1-12
Author(s):  
Xiong-zhi Wang ◽  
Wenliang Zhou

In this article, we investigate a joint pricing and inventory problem for a retailer selling fresh agriproducts (FAPs) with two-period shelf lifetime in a dynamic stochastic setting, where new and old FAPs are on sale simultaneously. At the beginning of each period the retailer makes ordering decision for new FAP and sets regular and discount price for new and old inventories, respectively. After demand realization, the expired leftover is disposed and unexpired inventory is carried to the next period, continuing selling. Unmet demand of all FAPs is backordered. The objective is to maximize the total expected discount profit over the whole planning horizon. We present a price-dependent, stochastic dynamic programming model taking into account zero lead time, linear ordering costs, inventory holding, and backlogging costs, as well as disposal cost. Considering the influence of the perishability, we integrate a Multinomial Logit (MNL) choice model to describe the consumer behavior on purchasing fresh or nonfresh product. By way of the inverse of the price vector, the original formulation can be transferred to be jointly concave and tractable. Finally we characterize the optimal policy and develop effective methods to solve the problem and conduct a simple numerical illustration.


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