Simulation-Based Genetic Algorithm for Cross-Docking Center Operation Optimization under Supply Disruptions

2011 ◽  
Vol 201-203 ◽  
pp. 1103-1106
Author(s):  
Yi Fan Wu
Keyword(s):  
Genetic Algorithm ◽  
Customer Service ◽  
Performance Optimization ◽  
Transportation Cost ◽  
Search Space ◽  
Inventory Level ◽  
Cost Rate ◽  
Supply Disruptions ◽  
Cross Docking ◽  
Customer Service Level

Practical performance optimization of a cross-docking center has been rare in the literature so far. The measures representing operation efficiency are average inventory level and transportation cost rate, while average backorder level represents the customer service level. In this paper, a simulation optimization problem is considered and a solution framework has been developed by integrating simulation, genetic algorithm (GA) and smart computing budget allocation (SCBA) to find an optimized solution. Moreover, supply disruptions are considered in the simulation model. This problem has huge search space even for medium-sized problem scenarios. To address this difficulty, the framework employs simulation to estimate the performance measures, GA to search for better design and SCBA to efficiently allocate the simulation budget.

scholarly journals An improved Genetic Algorithm For Fuzzy Production PlanningProblems with Application

2015 ◽  
Vol 1 (3) ◽  
pp. 390
Author(s):  
Jalal Abdulkareem Sultan ◽  
Omar Ramzi Jasim ◽  
Sarmad Abdulkhaleq Salih
Keyword(s):  
Genetic Algorithm ◽  
Customer Service ◽  
Fundamental Problem ◽  
Demand Forecasting ◽  
Fuzzy Model ◽  
Main Idea ◽  
Production Schedule ◽  
Improved Genetic Algorithm ◽  
Customer Service Level ◽  
Master Production Schedule

Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problem in operation and it can potentially lead to poor customer satisfaction.  In this paper, an improved Genetic Algorithm (IGA) is used to solving fuzzy multi-objective master production schedule (FMOMPS). The main idea is to integrate GA with local search operator. The FMOMPS was applied in the Cotton and medical gauzes plant in Mosul city. The application involves determine the gross requirements by demand forecasting using artificial neural networks. The IGA proved its efficiency in solving MPS problems compared with the genetic algorithm for fuzzy and non-fuzzy model, as the results clearly showed the ability of IGA to determine intelligently how much, when, and where the additional capacities (overtimes) are required such that the inventory can be reduced without affecting customer service level.

scholarly journals Adaptive inventory control system for material items with continuous non-stationary demand

2014 ◽  
Vol 5 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Martin Krajčovič ◽  
Dariusz Plinta
Keyword(s):  
Control System ◽  
Inventory Control ◽  
Customer Service ◽  
Service Level ◽  
Inventory Systems ◽  
Inventory Level ◽  
Inventory Analysis ◽  
Software Module ◽  
Large Numbers ◽  
Customer Service Level

Abstract This paper describes an algorithm of dynamic inventory control system for large numbers of material items with continuous non-stationary demand. It uses principles of pull inventory control systems, statistical inventory analysis and joint replenishment inventory systems. This algorithm was processed in software module (VBA for Excel) and applied in practice. The target of described algorithm is to keep an optimum inventory level and optimum customer service level in terms of inventory control of items with non-stationary demand.

Retail supply chain service levels: the role of inventory storage

2016 ◽  
Vol 29 (6) ◽  
pp. 887-902 ◽  
Author(s):  
Asif Salam ◽  
Farhad Panahifar ◽  
P.J. Byrne
Keyword(s):  
Supply Chain ◽  
Customer Service ◽  
Service Level ◽  
Retail Industry ◽  
Inventory Level ◽  
Content Type ◽  
Service Levels ◽  
Product Availability ◽  
Customer Service Level ◽  
The Relationship

Purpose In today’s competitive retail industry the most critical success factor is customer service which is indicated by product availability. It is argued that in the retail industry, product availability is an important measure of quality. The single most vital decision that every retailer needs to make is, how to maximize service level while keeping minimum inventory level. The purpose of this paper is to explain and demonstrate the relationship between inventory level and customer service level. Design/methodology/approach This study examines an inventory system utilizing a simulation model based on company data obtained from a retail fast-moving-consumer goods chain operating in Thailand. Findings The results suggest that the achievement of a responsive service level is dependent on managing an efficient supply chain in addition to logistics cost reductions. The findings also reveal the effect the inventory level has on the service level. From the findings of this study, demand variability and service level have been found to have the most significant influence on the inventory level. From the findings, it can also be shown that real and accurate information is very important for service supply chains. Practical implications The paper promotes the importance of having an appropriate inventory management policy for a retail chain which should be driven by retail companies in order to better balance inventory and service levels. Originality/value The relationship between the inventory level and customer service level lead to different outcomes at different combinations of inventory and service levels. Significant relationships were found between inventory and service levels.

scholarly journals Service-oriented performance of inventory models with partial information on unimodal demand lead-time distributions

2020 ◽  
Author(s):  
Gerrit K. Janssens ◽  
Lotte Verdonck ◽  
Katrien Ramaekers
Keyword(s):  
Customer Service ◽  
Lead Time ◽  
Partial Information ◽  
Service Level ◽  
Inventory Level ◽  
Worst Case ◽  
Point Distribution ◽  
Safety Stock ◽  
Demand Distribution ◽  
Customer Service Level

Facing uncertainty in demand, companies try to avoid stock-outs by holding safety inventories, depending on a pre-set customer service level. The knowledge of the demand distribution during lead-time serves to determine the safety inventory level. Many times the distribution is not fully known, except maybe for its range, mean or variance. However literature shows that the performance of holding safety stock strongly depends on the characteristics of the distribution. One option is to protect against the worst case distribution given some information like range or moments. But this worst case is a two-point distribution, bringing unbelief to managers that such an occurrence would ever appear. Mostly they share the opinion that the demand distribution is unimodal. This research develops a technique to derive the safety stock for unimodal demand distributions of which the mode either is known or can be estimated. In this way, the managers obtain solutions to the decision problem including a higher belief that the related type of distribution might appear in practice.

Minimization of total trim loss occurring in pipe cutting in shipbuilding with genetic algorithm

2021 ◽  
pp. 147509022199169
Author(s):  
Abdullah Türk ◽  
Dursun Saral ◽  
Murat Özkök ◽  
Ercan Köse
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Search Space ◽  
Cutting Process ◽  
Genetic Operators ◽  
Critical Stage ◽  
Different Types ◽  
Trim Loss ◽  
Pipe Systems

Outfitting is a critical stage in the shipbuilding process. Within the outfitting, the construction of pipe systems is a phase that has a significant effect on time and cost. While cutting the pipes required for the pipe systems in shipyards, the cutting process is usually performed randomly. This can result in large amounts of trim losses. In this paper, we present an approach to minimize these losses. With the proposed method it is aimed to base the pipe cutting process on a specific systematic. To solve this problem, Genetic Algorithms (GA), which gives successful results in solving many problems in the literature, have been used. Different types of genetic operators have been used to investigate the search space of the problem well. The results obtained have proven the effectiveness of the proposed approach.

What should be lean buffer threshold for the forward-reserve warehouse?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bhavin Shah
Keyword(s):  
Mathematical Model ◽  
Customer Service ◽  
Value Added ◽  
Service Level ◽  
Buffer Size ◽  
Value Stream Mapping ◽  
Content Type ◽  
Customer Service Level ◽  
The Impact ◽  
Just Right

PurposeThe assorted piece-wise retail orders in a cosmetics warehouse are fulfilled through a separate fast-picking area called Forward Buffer (FB). This study determines “just-right” size of FB to ensure desired Customer Service Level (CSL) at least storage wastages. It also investigates the impact of FB capacity and demand variations on FB leanness.Design/methodology/approachA Value Stream Mapping (VSM) tool is applied to analyse the warehouse activities and mathematical model is implemented in MATLAB to quantify the leanness at desired CSL. A comprehensive framework is developed to determine lean FB buffer size for a Retail Distribution Centre (RDC) of a cosmetics industry.FindingsThe CSL increases monotonically; however, the results concerning spent efforts towards CSL improvement gets diminished with raised demand variances. The desired CSL can be achieved at least FB capacity and fewer Storage Waste (SW) as it shifts towards more lean system regime. It is not possible to improve Value Added (VA) time beyond certain constraints and therefore, it is recommended to reduce Non-Value Added (NVA) order processing activities to improve leanness.Research limitations/implicationsThis study determines “just-right” capacity and investigates the impact of buffer and demand variations on leanness. It helps managers to analyse warehouse processes and design customized distribution policies in food, beverage and retail grocery warehouse.Practical implicationsProposed buffering model offers customized strategies beyond pre-set CSL by varying it dynamically to reduce wastages. The mathematical model deriving lean sizing and mitigation guidelines are constructive development for managers.Originality/valueThis research provides an inventive approach of VSM model and Mathematical algorithm endorsing lean thinking to design effective buffering policies in a forward warehouse.

scholarly journals A literature review on multi-echelon inventory management: the case of pharmaceutical supply chain

2018 ◽  
Vol 200 ◽  
pp. 00013 ◽  
Author(s):  
Nouçaiba Sbai ◽  
Abdelaziz Berrado
Keyword(s):  
Supply Chain ◽  
Customer Service ◽  
Inventory Management ◽  
Raw Materials ◽  
Integrated Approach ◽  
Service Level ◽  
Pharmaceutical Products ◽  
Management Problem ◽  
Pharmaceutical Supply Chain ◽  
Customer Service Level

Inventory management remains a key challenge in supply chain management. Many companies recognize the benefits of a good inventory management system. An effective inventory management helps reaching a high customer service level while dealing with demand variability. In a complex supply chain network where inventories are found across the entire system as raw materials or finished products, the need for an integrated approach for managing inventory had become crucial. Modelling the system as a multi-echelon inventory system allows to consider all the factors related to inventory optimization. On the other hand, the high criticality of the pharmaceutical products makes the need for a sophisticated supply chain inventory management essential. The implementation of the multi-echelon inventory management in such supply chains helps keeping the stock of pharmaceutical products available at the different installations. This paper provides an insight into the multi-echelon inventory management problem, especially in the pharmaceutical supply chain. A classification of several multi-echelon inventory systems according to a set of criteria is provided. A synthesis of multiple multi-echelon pharmaceutical supply chain problems is elaborated.

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