scholarly journals The single-manufacturer single-retailer integrated production-delivery lot sizing model with production capacity under stochastic lead time demand

Procedia CIRP ◽  
2019 ◽  
Vol 83 ◽  
pp. 528-533 ◽  
Author(s):  
Xuefang Sun ◽  
Renqian Zhang
Keyword(s):  
Lead Time ◽  
Lot Sizing ◽  
Production Capacity ◽  
Integrated Production ◽  
Stochastic Lead Time

scholarly journals The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xuefang Sun
Keyword(s):  
Genetic Algorithm ◽  
Lead Time ◽  
Production Capacity ◽  
Solution Procedure ◽  
Managerial Implication ◽  
Optimal Production ◽  
Integrated Production ◽  
Delivery Model ◽  
Multiple Buyers ◽  
Exhaustive Method

In this paper, we consider an integrated production-delivery model in which a vendor supplies the same product to multiple buyers. Unlike existing study, in this proposed model, we assume that the sum of all buyers’ demand rates is larger than the vendor’s production rate under normal work, but less than that under overtime. All buyers are independent of each other. For each buyer, the lead time demand is stochastic and the shortage during lead time is permitted. The main objective of this model is to determine the optimal production and delivery policies and the optimal overtime strategy, which minimize the joint expected annual cost of the system. Based on the genetic algorithm, we develop a solution procedure to find the optimal production, delivery, and overtime decision of this model. Computational experiments show the error rate between the objective values obtained by the proposed solution procedure and the solutions solved by the exhaustive method. The results indicate that the proposed mixed genetic algorithm is more effective and adoptable in comparison with the exhaustive method as it can be able to calculate the optimal solutions for at least 96% for the instances. Ultimately, an adequate numerical example is given to show the detailed process of the solution procedure, and sensitivity analysis of main parameters with managerial implication is discussed.

scholarly journals Integrated Production-Delivery Lot Sizing Model with Limited Production Capacity and Transportation Cost considering Overtime Work and Maintenance Time

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Renqian Zhang ◽  
Xuefang Sun
Keyword(s):  
Supply Chain ◽  
Numerical Experiment ◽  
Lot Sizing ◽  
Production Capacity ◽  
Transportation Cost ◽  
Solution Procedure ◽  
Sensitive Analysis ◽  
Integrated Production ◽  
Overtime Work ◽  
Maintenance Time

An extension of the integrated production-delivery lot sizing model with limited production capacity and transportation cost is investigated. We introduce the factor of overtime work into the model to improve the manufacturer’s production. In addition, when finishing a lot, the manufacturer has maintenance time to maintain and repair equipment for ensuring that the supply chain is operating continuously. By analyzing the integrated model, the solution procedure is provided to determine the optimal delivery and order policy. We conduct a numerical experiment and give sensitive analysis by varying some parameters to illustrate the problem and its solution procedure.

Coordinating lot sizing and integrated production and distribution scheduling with batch delivery and holding cost

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maedeh Bank ◽  
Mohammad Mahdavi Mazdeh ◽  
Mahdi Heydari ◽  
Ebrahim Teimoury
Keyword(s):  
Supply Chain ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Time Interval ◽  
Content Type ◽  
Integrated Production ◽  
Holding Costs ◽  
Integrated Production And Distribution ◽  
Distribution Scheduling ◽  
Production And Distribution

PurposeThe aim of this paper is to present a method for finding the optimum balance between sequence-dependent setup costs, holding costs, delivery costs and delay penalties in an integrated production–distribution system with lot sizing decisions.Design/methodology/approachTwo mixed integer linear programming models and an optimality property are proposed for the problem. Since the problem is NP-hard, a genetic algorithm reinforced with a heuristic is developed for solving the model in large-scale settings. The algorithm parameters are tuned using the Taguchi method.FindingsThe results obtained on randomly generated instances reveal a performance advantage for the proposed algorithm; it is shown that lot sizing can reduce the average cost of the supply chain up to 11.8%. Furthermore, the effects of different parameters and factors of the proposed model on supply chain costs are examined through a sensitivity analysis.Originality/valueAlthough integrated production and distribution scheduling in make-to-order industries has received a great deal of attention from researchers, most researchers in this area have treated each order as a job processed in an uninterrupted time interval, and no temporary holding costs are assumed. Even among the few studies where temporary holding costs are taken into consideration, none has examined the effect of splitting an order at the production stage (lot sizing) and the possibility of reducing costs through splitting. The present study is the first to take holding costs into consideration while incorporating lot sizing decisions in the operational production and distribution problem.

scholarly journals An Inventory Model for Deteriorating Drugs with Stochastic Lead Time

2018 ◽  
Vol 15 (12) ◽  
pp. 2772 ◽  
Author(s):  
Jian Li ◽  
Lu Liu ◽  
Hao Hu ◽  
Qiuhong Zhao ◽  
Libin Guo
Keyword(s):  
Shelf Life ◽  
Inventory Management ◽  
Lead Time ◽  
Service Level ◽  
Inventory Model ◽  
Effective Management ◽  
Product Availability ◽  
Stochastic Lead Time ◽  
Random Lead Time ◽  
The Right

Inventory management of deteriorating drugs has attracted considerable attention recently in hospitals. Drugs are a kind of special product. Two characteristics of some drugs are the shorter shelf life and high service level. This causes hospitals a great deal of difficulty in inventory management of perishable drugs. On one hand, hospitals should increase the drug inventory to achieve a higher service level. On the other hand, hospitals should decrease the drug inventory because of the short shelf life of drugs. An effective management of pharmaceuticals is required to ensure 100% product availability at the right time, at the right cost, in good conditions to the right customers. This requires a trade-off between shelf-life and service level. In addition, many uncontrollable factors can lead to random lead time of drugs. This paper focuses on deteriorating drugs with stochastic lead time. We have established a stochastic lead time inventory model for deteriorating drugs with fixed demand. The lead time obeyed a certain distribution function and shortages were allowed. This model also considered constraints on service level, stock space and drug shelf life. Through the analysis of the model, the shelf life of drugs and service level were weighted in different lead time distributions. Empirical analysis and sensitivity analysis were given to get reach important conclusions and enlightenment.

scholarly journals Lot-sizing problem with several production centers

2005 ◽  
Vol 25 (3) ◽  
pp. 479-492 ◽  
Author(s):  
Franklina Maria Bragion de Toledo ◽  
André Luís Shiguemoto
Keyword(s):  
Dynamic Programming ◽  
Lot Sizing ◽  
Dynamic Programming Algorithm ◽  
Production Capacity ◽  
Efficient Implementation ◽  
Programming Algorithm ◽  
Future Research ◽  
Production Environment ◽  
Lot Sizing Problem ◽  
Forward Dynamic Programming

In this paper, a case study is carried out concerning the lot-sizing problem involving a single item production planning in several production centers that do not present capacity constraints. Demand can be met with backlogging or not. This problem results from simplifying practical problems, such as the material requirement planning (MRP) system and also lot-sizing problems with multiple items and limited production capacity. First we propose an efficient implementation of a forward dynamic programming algorithm for problems with one single production center. Although this does not reduce its complexity, it has shown to be rather effective, according to computational tests. Next, we studied the problem with a production environment composed of several production centers. For this problem two algorithms are implemented, the first one is an extension of the dynamic programming algorithm for one production center and the second one is an efficient implementation of the first algorithm. Their efficiency are shown by computational testing of the algorithms and proposals for future research are presented.

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