Dynamic-programming-based inequalities for the capacitated lot-sizing problem

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.

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A variable neighborhood search for multi-family capacitated lot-sizing problem

Electronic Notes in Discrete Mathematics ◽

10.1016/j.endm.2018.03.016 ◽

2018 ◽

Vol 66 ◽

pp. 119-126 ◽

Cited By ~ 1

Author(s):

Jerzy Duda ◽

Adam Stawowy

Keyword(s):

Variable Neighborhood Search ◽

Lot Sizing ◽

Neighborhood Search ◽

Lot Sizing Problem ◽

Capacitated Lot Sizing

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

Journal of Modelling in Management ◽

10.1108/jm2-10-2018-0169 ◽

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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Lot-sizing problem with several production centers

Pesquisa Operacional ◽

10.1590/s0101-74382005000300010 ◽

2005 ◽

Vol 25 (3) ◽

pp. 479-492 ◽

Cited By ~ 1

Author(s):

Franklina Maria Bragion de Toledo ◽

André Luís Shiguemoto

Keyword(s):

Dynamic Programming ◽

Lot Sizing ◽

Dynamic Programming Algorithm ◽

Production Capacity ◽

Efficient Implementation ◽

Programming Algorithm ◽

Future Research ◽

Production Environment ◽

Lot Sizing Problem ◽

Forward Dynamic Programming

In this paper, a case study is carried out concerning the lot-sizing problem involving a single item production planning in several production centers that do not present capacity constraints. Demand can be met with backlogging or not. This problem results from simplifying practical problems, such as the material requirement planning (MRP) system and also lot-sizing problems with multiple items and limited production capacity. First we propose an efficient implementation of a forward dynamic programming algorithm for problems with one single production center. Although this does not reduce its complexity, it has shown to be rather effective, according to computational tests. Next, we studied the problem with a production environment composed of several production centers. For this problem two algorithms are implemented, the first one is an extension of the dynamic programming algorithm for one production center and the second one is an efficient implementation of the first algorithm. Their efficiency are shown by computational testing of the algorithms and proposals for future research are presented.

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