Integrated production and transportation scheduling with order-dependent inventory holding costs

2021 ◽  
pp. 105477
Author(s):  
Xianyan Yang ◽  
Zhixue Liu ◽  
Feng Li ◽  
Zhou Xu
Keyword(s):  
Integrated Production ◽  
Holding Costs ◽  
Transportation Scheduling ◽  
Inventory Holding

scholarly journals Integrated Production and Delivery with Inventory Holding Costs

2016 ◽  
Vol 49 (12) ◽  
pp. 910-915
Author(s):  
Alessandro Agnetis ◽  
Mohamed Ali Aloulou ◽  
Mikhail Y. Kovalyov
Keyword(s):  
Integrated Production ◽  
Holding Costs ◽  
Inventory Holding

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.

A Memetic Algorithm for Integrated Production Distribution Problem in a Supply Chain

2021 ◽  
pp. 198-224
Author(s):  
Nihan Kabadayi
Keyword(s):  
Supply Chain ◽  
Memetic Algorithm ◽  
Real Life ◽  
Data Sets ◽  
Distribution Problem ◽  
Setup Cost ◽  
Integrated Production ◽  
Holding Costs ◽  
Life Problems ◽  
Production Distribution

Supply chain is a complex system in which most of the activities are inter-related, and changes in one of these activities can affect the performance of the other processes. Thus, integrated management strategies in a supply chain can yield considerable advantages throughout the system as supply chain members and customers become more integrated. In this study, a memetic algorithm is proposed to solve the integrated production-distribution problem. The objective of the problem is to find optimal production quantity, customer delivery quantity, and schedule to minimize the total system cost, which is composed of production setup cost and variable production cost, inventory holding costs, and distribution cost. The effectiveness of the proposed algorithm is tested on the existing data sets. According to test results, the proposed algorithm is a very effective method to solve integrated production-distribution problems. To assess to benefits and applicability of the method on the real-life problems, a case study is conducted in a Turkish water manufacturing company.

MATHEMATICAL MODEL FOR INVENTORY CONTROL PROBLEM USING IMPRECISE PARAMETERS

2018 ◽  
Vol 6 (2) ◽  
pp. 07-12
Author(s):  
Neha Kumari ◽  
Manoj Kumar Mandal ◽  
Arun Prasad Burnwal
Keyword(s):  
Control Problem ◽  
Inventory Control ◽  
Geometric Programming ◽  
Programming Model ◽  
Holding Costs ◽  
Fuzzy Membership Functions ◽  
Inventory Control Problem ◽  
Set Up ◽  
Inventory Holding ◽  
Imprecise Parameters

In this paper, an inventory control problem is discussed using imprecise parameters. The fusion of geometric programming and fuzzy logic is used as imprecise parameters to solve inventory control problems. In inventory, holding costs, set-up costs, etc. may be flexible due to vague information. Fuzzy set theory is used to convert the inventory model crisp to fuzzy for producing flexible output. Compensatory operator is used to aggregate the fuzzy membership functions corresponding to fuzzy sets for fuzzy objectives and constraints. This aggregation gives the overall achievement function and the model known as fuzzy geometric programming model.  

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