Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: generalised outer approximation

2018 ◽  
Vol 6 (3) ◽  
pp. 237-257 ◽  
Author(s):  
Seyed Ashkan Hoseini Shekarabi ◽  
Abolfazl Gharaei ◽  
Mostafa Karimi
Keyword(s):  
Supply Chains ◽  
Lot Sizing ◽  
Outer Approximation ◽  
Multi Level

scholarly journals A Tabu List-Based Algorithm for Capacitated Multilevel Lot-Sizing with Alternate Bills of Materials and Co-Production Environments

2019 ◽  
Vol 9 (7) ◽  
pp. 1464 ◽  
Author(s):  
Alfonso Romero-Conrado ◽  
Jairo Coronado-Hernandez ◽  
Gregorio Rius-Sorolla ◽  
José García-Sabater
Keyword(s):  
Lot Sizing ◽  
Medium Size ◽  
Exact Methods ◽  
Operations Planning ◽  
Material Requirements Planning ◽  
Tabu List ◽  
Production Environments ◽  
Lot Sizes ◽  
Multi Level ◽  
Definition Of

The definition of lot sizes represents one of the most important decisions in production planning. Lot-sizing turns into an increasingly complex set of decisions that requires efficient solution approaches, in response to the time-consuming exact methods (LP, MIP). This paper aims to propose a Tabu list-based algorithm (TLBA) as an alternative to the Generic Materials and Operations Planning (GMOP) model. The algorithm considers a multi-level, multi-item planning structure. It is initialized using a lot-for-lot (LxL) method and candidate solutions are evaluated through an iterative Material Requirements Planning (MRP) procedure. Three different sizes of test instances are defined and better results are obtained in the large and medium-size problems, with minimum average gaps close to 10.5%.

scholarly journals FLOWER POLLINATION ALGORITHM FOR MULTI LEVEL LOT SIZING OPTIMIZATION

2021 ◽  
Vol 9 (1) ◽  
pp. 127-133
Author(s):  
V. V. D. Sahithi, M. Srinivasa Rao, C. S. P. Rao
Keyword(s):  
Lot Sizing ◽  
Complex Problem ◽  
Flower Pollination Algorithm ◽  
Customer Requirements ◽  
Proper Place ◽  
Flower Pollination ◽  
Multi Level ◽  
Simulation Results ◽  
Exact Amount ◽  
Better Than

In this competitive and constantly changing world, meeting the customer requirements within less time by providing less cost is extremely tricky task. This is only possible by optimizing all the different parameters in its life cycle. Here Optimizing the inventory plays a major role.Maintaining the exact amount of inventory, at proper place, in appropriate level is a challenging task for production managers. When we work on Multi level environments this problem becomes even more complex.So, to optimize this kind of problems we applied binary form of Flower Pollination algorithm to solve this complex problem. we solved different inventory lot sizing problems with this FP algorithm and compared the results with genetic algorithm and other algorithms. In all the scenarios our simulation results shown that FP algorithm is better than other algorithms.                       

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