MINIMALISASI BIAYA SIMPAN DAN BIAYA SETUP PADA MULTIPLE PRODUK: SIMULASI DENGAN CAPACITATED LOT SIZING PROBLEM

2019 ◽  
Vol 4 (2) ◽  
pp. 205-214
Author(s):  
Erika Fatma
Keyword(s):  
Production Cost ◽  
Lot Sizing ◽  
Setup Time ◽  
Production Costs ◽  
Total Production ◽  
Product Cycle ◽  
Lot Size ◽  
Setup Costs ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing

Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%.  Keyword: Lot size, CLSP, Total production cost.

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.

Tactical Production and Lot Size Planning with Lifetime Constraints: A Comparison of Model Formulations

2017 ◽  
Vol 34 (05) ◽  
pp. 1750019 ◽  
Author(s):  
Andrea Raiconi ◽  
Julia Pahl ◽  
Monica Gentili ◽  
Stefan Voß ◽  
Raffaele Cerulli
Keyword(s):  
Finite Number ◽  
Lot Sizing ◽  
Classical Problem ◽  
Lot Size ◽  
Experimental Phase ◽  
Classical Version ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing ◽  
Lot Sizes ◽  
Production Resources

In this work, we face a variant of the capacitated lot sizing problem. This is a classical problem addressing the issue of aggregating lot sizes for a finite number of discrete periodic demands that need to be satisfied, thus setting up production resources and eventually creating inventories, while minimizing the overall cost. In the proposed variant we take into account lifetime constraints, which model products with maximum fixed shelflives due to several possible reasons, including regulations or technical obsolescence. We propose four formulations, derived from the literature on the classical version of the problem and adapted to the proposed variant. An extensive experimental phase on two datasets from the literature is used to test and compare the performance of the proposed formulations.

scholarly journals Iterated Local Search for Foundry Lotsizing and Scheduling Problem with Setup Costs

2017 ◽  
Vol 17 (4) ◽  
pp. 161-164 ◽  
Author(s):  
A. Stawowy ◽  
J. Duda
Keyword(s):  
Local Search ◽  
Lot Sizing ◽  
Iterated Local Search ◽  
Setup Costs ◽  
Lot Sizing Problem ◽  
The Family ◽  
Local Search Procedure ◽  
Capacitated Lot Sizing ◽  
Commercial Solver ◽  
Lotsizing And Scheduling

Abstract The paper presents a novel Iterated Local Search (ILS) algorithm to solve multi-item multi-family capacitated lot-sizing problem with setup costs independent of the family sequence. The model has a direct application to real production planning in foundry industry, where the goal is to create the batches of manufactured castings and the sequence of the melted metal loads to prevent delays in delivery of goods to clients. We extended existing models by introducing minimal utilization of furnace capacity during preparing melted alloy. We developed simple and fast ILS algorithm with problem-specific operators that are responsible for the local search procedure. The computational experiments on ten instances of the problem showed that the presence of minimum furnace utilization constraint has great impact on economic and technological conditions of castings production. For all test instances the proposed heuristic is able to provide the results that are comparable to state-of-the art commercial solver.

Immaterial Cost and Production: Maximum Production Cost Level Through Marginal Approach

2020 ◽  
Vol 8 (2) ◽  
pp. 128-149
Author(s):  
Dini Maulana Lestari
Keyword(s):  
Quantitative Study ◽  
Marginal Cost ◽  
Production Cost ◽  
Maximum Level ◽  
Production Costs ◽  
Total Production ◽  
Sugar Factory ◽  
Maximum Production ◽  
Cost Approach ◽  
South Sulawesi

This paper will discuss about the immaterial costs and production yields at one of the refined sugar factory companies in Makassar, South Sulawesi. The theory is based on the fact that Immaterial is a cost that is almsgiving, meaning costs that are outside of the basic costs of the company in producing production, so this research aims to find out: (1) what is the production cost needed to produce this production, (2) the maximum level of production at company from 2013 to 2017. This type of research is a quantitative study because it uses a questionnaire in the form of values ​​that are processed using the marginal cost approach formula. The results of the analysis show that (1) the maximum level of production costs occurred in 2016 amounting to 6,912 with an Immaterial cost of Rp. 2,481,796,800 and the total production produced is 359,077.3 tons (2) The required workforce with the total production produced is 359,077.3 tones of 180 people including the maximum production point which means that the lowest value is achieved (optimal).    

Designing an uncertain bi-objective green leagile capacitated lot sizing problem considering FM/M/C queue system

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Masoud Rabbani ◽  
Soroush Aghamohamadi Bosjin ◽  
Neda Manavizadeh ◽  
Hamed Farrokhi-Asl
Keyword(s):  
Mathematical Model ◽  
Solution Method ◽  
Lot Sizing ◽  
Test Problems ◽  
Content Type ◽  
Queue System ◽  
Proposed Model ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing ◽  
To Receive

Purpose This paper aims to present a novel bi-objective mathematical model for a production-inventory system under uncertainty. Design/methodology/approach This paper addresses agile and lean manufacturing concepts alongside with green production methods to design an integrated capacitated lot sizing problem (CLSP). From a methodological perspective, the problem is solved in three phases. In the first step, an FM/M/C queuing system is used to minimize the number of customers waited to receive their orders. In the second step, an effective approach is applied to deal with the fuzzy bi-objective model and finally, a hybrid metaheuristic algorithm is used to solve the problem. Findings Some numerical test problems and sensitivity analyzes are conducted to measure the efficiency of the proposed model and the solution method. The results validate the model and the performance of the solution method compared to Gams results in small size test problems and prove the superiority of the hybrid algorithm in comparison with the other well-known metaheuristic algorithms in large size test problems. Originality/value This paper presents a novel bi-objective mathematical model for a CLSP under uncertainty. The proposed model is conducted on a practical case and several sensitivity analysis are conducted to assess the behavior of the model. Using a queue system, this problem aims to reduce the items waited in the queue to receive service. Two objective functions are considered to maximize the profit and minimize the negative environmental effects. In this regard, the second objective function aims to reduce the amount of emitted carbon.

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