Production Planning Considering Transfer Lot Size

2010 ◽  
Vol 44-47 ◽  
pp. 552-556
Author(s):  
Zhi Cong Zhang ◽  
Kai Shun Hu ◽  
Hui Yu Huang ◽  
Shuai Li
Keyword(s):  
Production Planning ◽  
Performance Measures ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Production Plan ◽  
Lot Size ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Lot Sizing Problem ◽  
Plan Change

Traditional methods conduct production planning and scheduling separately and solve transfer lot sizing problem between these two steps. Unfortunately, this may result in infeasibility in planning and scheduling. We take into account transfer lot size in production planning to obtain the consistency and to eliminate the gap between planning and real production. We present the detailed Transfer Lot-Based Model with mixed integer programming. Experiments show that performance measures of a production plan change remarkably with increasing of transfer lot size.

scholarly journals Coordinated Production Planning and Scheduling Problem in a Foundry

2017 ◽  
Vol 17 (3) ◽  
pp. 133-138
Author(s):  
A. Stawowy ◽  
J. Duda
Keyword(s):  
Production Planning ◽  
Programming Model ◽  
Mixed Integer ◽  
Medium Size ◽  
Scheduling Problem ◽  
Planning And Scheduling ◽  
Alloy Casting ◽  
Production Planning And Scheduling ◽  
Multiple Cores ◽  
Molding Shop

Abstract In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data simulating actual production parameters in one of the medium size foundry.

Optimization Methods for Lot-Sizing Problem in an Automated Foundry

2013 ◽  
Vol 58 (3) ◽  
pp. 863-866 ◽  
Author(s):  
J. Duda ◽  
A. Stawowy
Keyword(s):  
Production Planning ◽  
Lot Sizing ◽  
Planning Horizon ◽  
Optimization Methods ◽  
Mixed Integer ◽  
Planning Problem ◽  
Lot Size ◽  
Mip Model ◽  
Production Planning Problem ◽  
Problem Instances

Abstract In the paper we studied a production planning problem in a mid-size foundry that provides tailor-made cast products in small lots for a large number of clients. Assuming that a production bottleneck is the furnace, a mixed-integer programming (MIP) model is proposed to determine the lot size of the items and the required alloys to be produced during each period of the finite planning horizon that is subdivided into smaller periods. As using an advanced commercial MIP solvers may be impractical for more complex and large problem instances, we proposed and compared a few computational intelligence heuristics i.e. tabu search, genetic algorithm and differential evolution. The examination showed that heuristic approaches can provide a good compromise between speed and quality of solutions and can be used in real-world production planning.

scholarly journals Application of Interval Arithmetic to Production Planning in a Foundry

2017 ◽  
Vol 17 (1) ◽  
pp. 41-44
Author(s):  
J. Duda ◽  
A. Stawowy
Keyword(s):  
Production Planning ◽  
Interval Arithmetic ◽  
Lot Sizing ◽  
Accurate Information ◽  
Test Problems ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Scheduling Model ◽  
Novel Approach ◽  
Lot Sizing And Scheduling

Abstract A novel approach for treating the uncertainty about the real levels of finished products during production planning and scheduling process is presented in the paper. Interval arithmetic is used to describe uncertainty concerning the production that was planned to cover potential defective products, but meets customer’s quality requirement and can be delivered as fully valuable products. Interval lot sizing and scheduling model to solve this problem is proposed, then a dedicated version of genetic algorithm that is able to deal with interval arithmetic is used to solve the test problems taken from a real-world example described in the literature. The achieved results are compared with a standard approach in which no uncertainty about real production of valuable castings is considered. It has been shown that interval arithmetic can be a valuable method for modeling uncertainty, and proposed approach can provide more accurate information to the planners allowing them to take more tailored decisions.

scholarly journals Firefly Algorithm: Minimizing Cost on Single-Level Lot-Sizing Problem

2018 ◽  
Vol 3 (1) ◽  
pp. 55-63
Author(s):  
Siti Hafawati Jamaluddin ◽  
Nurul Azleeka Zulkipli ◽  
Norwaziah Mahmud ◽  
Nur Syuhada Muhamat Pazil
Keyword(s):  
Production Planning ◽  
Production Cost ◽  
Firefly Algorithm ◽  
Lot Sizing ◽  
Planning Horizon ◽  
Production Plan ◽  
Setup Cost ◽  
Single Level ◽  
Lot Sizing Problem ◽  
Industrial Company

Nowadays, the industrial company plays a very important role to our country. However, the manufacturer industry has big issues in the production planning which called planning horizon where, the lot-sizing problem is one of the most important issues in the production planning area. In lot-sizing problem, the manufacturers are facing the problems in determining the setup cost when there is no consistency and efficiency in organizing the production plan. From the problem emerge, the minimum of production cost is determined by using firefly algorithm. From the minimum production cost obtained, the optimal setup cost on single-level lot-sizing problem is defined. In this study, the result is obtained by using MATLAB R2017a software to minimize the production cost on single-level lot-sizing problem where the minimum production cost is are for one month is $154 while, the minimum production cost for 12 months is $1760.89. From those minimum total cost obtained by using firefly algorithm, the optimal setup cost for one month is $86.83 while optimal setup cost for 12 months are $86.51, $86.81, $88.30, $95.39, $112.01, $102.92, $93.30, $85.90, $106.50, $85.77, $99.46 and $115.30 respectively. As a conclusion, firefly algorithm is applicable to use in minimizing production cost on single-level lot-sizing problem since the result obtained gives the better solution compared to the exact solution

scholarly journals A New Formulation for the Capacitated Lot Sizing Problem with Batch Ordering Allowing Shortages

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 878 ◽  
Author(s):  
Yajaira Cardona-Valdés ◽  
Samuel Nucamendi-Guillén ◽  
Rodrigo E. Peimbert-García ◽  
Gustavo Macedo-Barragán ◽  
Eduardo Díaz-Medina
Keyword(s):  
Lot Sizing ◽  
Mixed Integer ◽  
Lot Size ◽  
Penalty Cost ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing ◽  
Batch Ordering ◽  
New Formulation ◽  
Production Resources

This paper addresses the multi-product, multi-period capacitated lot sizing problem. In particular, this work determines the optimal lot size allowing for shortages (imposed by budget restrictions), but with a penalty cost. The developed models are well suited to the usually rather inflexible production resources found in retail industries. Two models are proposed based on mixed-integer formulations: (i) one that allows shortage and (ii) one that forces fulfilling the demand. Both models are implemented over test instances and a case study of a real industry. By investigating the properties of the obtained solutions, we can determine whether the shortage allowance will benefit the company. The experimental results indicate that, for the test instances, the fact of allowing shortages produces savings up to 17% in comparison with the model without shortages, whereas concerning the current situation of the company, these savings represent 33% of the total costs while preserving the revenue.

Research on production planning and scheduling based on improved collaborative optimization

2019 ◽  
Vol 27 (2) ◽  
pp. 99-111 ◽  
Author(s):  
Song Zheng ◽  
Jiaxin Gao ◽  
Jian Xu
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Production Efficiency ◽  
Collaborative Optimization ◽  
Production Plan ◽  
The Novel ◽  
Integration Algorithm ◽  
Planning And Scheduling ◽  
Integrated Optimization ◽  
Production Planning And Scheduling

The production planning is aimed at the formulation and distribution of the overall production plan, while the production scheduling focuses on the implementation of the specific production plan. It is very important to coordinate each other in order to promote the production efficiency of enterprises, but the integrated optimization of production planning and scheduling has great challenges. This article proposes the novel integrated optimization method of planning and scheduling based on improved collaborative optimization. An integrated model of planning and scheduling with collaborative optimization structure is established, and the detailed solution strategy of the novel integrated optimization algorithm is presented. At last, the simulation results show that the proposed integration algorithm of planning and scheduling is competitive in global optimization and practicality.

scholarly journals Developing a Multi-Stage Production Planning and Scheduling Model for a Small-Size Food and Beverage Company

2021 ◽  
Vol 54 (2) ◽  
pp. 273-281
Author(s):  
Güzin Tirkeş ◽  
Neşe Çelebi ◽  
Cenk Güray
Keyword(s):  
Production Planning ◽  
Programming Model ◽  
Profit Maximization ◽  
Mixed Integer ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Beverage Industry ◽  
Multi Stage ◽  
Food And Beverage ◽  
The Right

A great deal of research has been undertaken in recent years related to facility capacity expansion and production planning problems under deterministic and stochastic constraints in the literature. However, only a small portion of this work directly addresses the issues faced by the food and beverage industry, especially in small-sized enterprises. In this study, a Mixed-Integer Linear Programming model (MILP) is developed for production planning and scheduling decisions for a small-size company producing syrup and jam products. The main constraint is that the multiple syrup and jam production lines in the model share the same limited-capacity module designed for inventory planning. To this end, the present model offers an efficient solution for executing a multi-product, multi-period production line by finding the most satisfactory strategy to match the right product with the useable capacity leading to profit maximization. The present approach is capable of coping with varying demands by offering a detailed costing procedure and implementing an effective inventory model.

scholarly journals Mathematical modeling to optimize production planning and scheduling in a small foundry with multiple alternating furnaces

2021 ◽  
Vol 16 (04) ◽  
pp. 82-114
Author(s):  
Michael Ferreira Bertulucci ◽  
Giovanna Abreu Alves ◽  
Victor Claudio Bento de Camargo
Keyword(s):  
Mathematical Modeling ◽  
Lot Sizing ◽  
Load Capacity ◽  
Mixed Integer ◽  
Suitable Model ◽  
Extended Model ◽  
Lot Size ◽  
Planning And Scheduling ◽  
Actual Application ◽  
Lot Sizing And Scheduling

Purpose - This study presents an extension to a model in the literature for lot-sizing and scheduling in a small foundry with multiple alternate furnaces. The purpose of the model is to minimize delays and inventory costs. In addition, it determines the best use of the load capacity in the furnaces. Theoretical framework – Lot-sizing in foundries in the marketplace is a subject of academic interest due to its applicability and mathematical and computational complexity. Many papers address the production problem in foundries with a single furnace, however, few papers address the possibility of multiple furnaces. Design/methodology/approach - Mathematical modeling was used to represent the lot-sizing and scheduling problem in a small foundry. Data from the company's order books were collected and model validation questionnaires were applied. Findings - The extended model was able to generate good production plans at different planning horizons, with better performance than the current methods obtained by the company. Originality/value - the extension of the model contributes to the literature by addressing the existence of multiple non-simultaneous furnaces, a feature that has not been greatly explored. A comparison with other models is performed to indicate the most suitable model for actual application. Keywords: Alloys scheduling. Foundry. Lot size. Mixed integer programming.

scholarly journals Alternative Mathematical Models and Solution Approaches for Lot-Sizing and Scheduling Problems in the Brewery Industry: Analyzing Two Different Situations

2017 ◽  
Vol 2017 ◽  
pp. 1-18
Author(s):  
Tamara A. Baldo ◽  
Reinaldo Morabito ◽  
Maristela O. Santos ◽  
Luis Guimarães
Keyword(s):  
Lot Sizing ◽  
Mixed Integer ◽  
Scheduling Problems ◽  
Heuristic Solution ◽  
Planning And Scheduling ◽  
Technology Investment ◽  
Production Planning And Scheduling ◽  
Mip Models ◽  
Solution Methods ◽  
Result Analysis

This research proposes new approaches to deal with the production planning and scheduling problem in brewery facilities. Two real situations found in factories are addressed, which differ by considering (or not) the setup operations in tanks that provide liquid for bottling lines. Depending on the technology involved in the production process, the number of tank swaps is relevant (Case A) or it can be neglected (Case B). For both scenarios, new MIP (Mixed Integer Programming) formulations and heuristic solution methods based on these formulations are proposed. In order to evaluate the approach for Case A, we compare the results of a previous study with the results obtained in this paper. For the solution methods and the result analysis of Case B, we propose adaptations of Case A approaches yielding an alternative MIP formulation to represent it. Therefore, the main contributions of this article are twofold: (i) to propose alternative MIP models and solution methods for the problem in Case A, providing better results than previously reported, and (ii) to propose new MIP models and solution methods for Case B, analyzing and comparing the results and benefits for Case B considering the technology investment required.

Sign in / Sign up

Export Citation Format

Share Document