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

We discuss stochastic multi-item capacitated lot-sizing problems with and without setup carryovers (also known as link lot size), S-MICLSP and S-MICLSP-L. The two models are motivated from a real-world steel enterprise. To overcome the nonlinearity of the models, a piecewise linear approximation method is proposed. We develop a new fix-and-optimize (FO) approach to solve the approximated models. Compared with the existing FO approach(es), our FO is based on the concept of “k-degree-connection” for decomposing the problems. Furthermore, we also propose an integrative approach combining our FO and variable neighborhood search (FO-VNS), which can improve the solution quality of our FO approach by diversifying the search space. Numerical experiments are performed on the instances following the nature of realistic steel products. Our approximation method is shown to be efficient. The results also show that the proposed FO and FO-VNS approaches significantly outperform the recent FO approaches, and the FO-VNS approaches can be more outstanding on the solution quality with moderate computational effort.

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

Jurnal Riset Manajemen dan Bisnis (JRMB) Fakultas Ekonomi UNIAT ◽

10.36226/jrmb.v4i2.260 ◽

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.

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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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