Bin Packing Problem with Compatible Categories Utilizing an Enhanced Variable Neighborhood Search Algorithm

A company that transports goods to supply customers usually needs to plan the routes that the fleet must follow, since transportation means a high percentage of the value added to goods. The vehicles must be loaded with the products located in the warehouse to fulfill the orders requested by customers. Many enterprises use order batching and picking systems to improve the warehouse management. This chapter describes a novel algorithm based on the methodology of variable neighborhood search for the variable cost and size bin packing problem. This problem considers that the sizes and costs of the bins can be different and there is no correlation between them, which is a sensible assumption for the order batching process in many applications. A series of computational experiments were conducted with a set of hard instances to validate this approach. The results show that the proposed algorithm outperforms the state-of-the-art algorithm, and a statistical hypothesis test is used to support the obtained conclusions.

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Uma nova heurística baseada na meta-heurística VNS para o problema de agrupamento de entregas em veículos de uma frota heterogênea

TRANSPORTES ◽

10.14295/transportes.v19i3.213 ◽

2011 ◽

Vol 19 (3) ◽

pp. 75

Author(s):

Jorge Von Atzingen dos Reis ◽

Claudio Barbieri da Cunha

Keyword(s):

Variable Neighborhood Search ◽

Bin Packing ◽

Packing Problem ◽

Freight Rate ◽

Third Party ◽

Neighborhood Search ◽

Benchmark Problems ◽

Font Size ◽

Bin Packing Problem ◽

Dimensional Variable

Resumo: Este artigo trata do problema de distribuição física que envolve o agrupamento e a alocação de entregas a uma frota de veículos visando minimizar o frete total. Este problema surge em diferentes situações práticas em que os pontos a serem atendidos estão suficientemente próximos entre si de tal modo que as distâncias percorridas entre paradas consecutivas podem ser consideradas irrele-vantes para o custo total de entregas da frota e, portanto, podem ser desconsideradas para o cálculo dos fretes pagos a terceiros que rea-lizam esse serviço. O problema pode ser modelado como um problema de bin-packing unidimensional com bins de tamanho variável (do inglês Variable Sized Bin-Packing Problem, VSBPP), uma generalização do tradicional problema de bin-packing no qual bins (veículos) de diferentes capacidades e custos estão disponíveis para a alocação de um conjunto de objetos (cargas) de modo que o custo total dos bins (veículos) utilizados seja mínimo. Neste trabalho é proposta uma nova heurística baseada na Busca em Vizinhança Variável (do inglês Variable Neighborhood Search ou VNS) para a resolução desse problema. Experimentos computacionais com instâncias derivadas de problemas benchmarking da literatura evidenciam que essa nova heurística produz resultados melhores em tempos de processamento bastante reduzidos. Palavras-chave: busca em vizinhança variável, problema de agrupamento e alocação de entregas, meta-heurística Abstract: In this paper we deal with the physical distribution problem which comprises grouping and assigning deliveries to a hetero-geneous fleet of vehicles aiming to minimize the total freight cost. This problem arises in several practical situations in which the customers to be served are geographically close enough to each other such that distances traveled between consecutive stops can be regarded as irrelevant when compared to the overall vehicle costs, and thus not considered when establishing the freight rate to be paid to third-party carriers. The problem can be modeled as one-dimensional Variable Sized Bin-Packing Problem (VSBPP), a generalization of the traditional bin-packing problem, in which bins (vehicles) with different sizes and costs are available for the assignment of the objects (deliveries) such that the total cost of the used bins (vehicles) is minimized. A new heuristic based on VNS (Variable Neighborhood Search) is proposed to solve this problem. Computational experiments conducted using instances derived from benchmark problems from the literature evidence that our heuristic produces improved results in very short times. Keywords: variable neighborhood search, variable sized bin-packing problem, metaheuristic.

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Solving the Two-Dimensional Bin-Packing Problem with Variable Bin Sizes by Greedy Randomized Adaptive Search Procedures and Variable Neighborhood Search

Computer Aided Systems Theory – EUROCAST 2011 - Lecture Notes in Computer Science ◽

10.1007/978-3-642-27549-4_58 ◽

2012 ◽

pp. 456-463 ◽

Cited By ~ 3

Author(s):

Andreas M. Chwatal ◽

Sandro Pirkwieser

Keyword(s):

Variable Neighborhood Search ◽

Bin Packing ◽

Packing Problem ◽

Neighborhood Search ◽

Two Dimensional ◽

Adaptive Search ◽

Bin Packing Problem

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A Reduced Variable Neighborhood Search Approach to the Heterogeneous Vector Bin Packing Problem

Information Technology And Control ◽

10.5755/j01.itc.50.4.29009 ◽

2021 ◽

Vol 50 (4) ◽

pp. 808-826

Author(s):

Đorđe Stakić ◽

Miodrag Živković ◽

Ana Anokić

Keyword(s):

Variable Neighborhood Search ◽

Bin Packing ◽

Optimization Problems ◽

Packing Problem ◽

Neighborhood Search ◽

Two Dimensional ◽

Total Cost ◽

Bin Packing Problem ◽

Benchmark Instances ◽

Search Approach

The two-dimensional heterogeneous vector bin packing problem (2DHet-VBPP) consists of packing the set of items into the set of various type bins, respecting their two resource limits. The problem is to minimize the total cost of all bins. The problem, known to be NP-hard, can be formulated as a pure integer linear program, but optimal solutions can be obtained by the CPLEX Optimizer engine only for small instances. This paper proposes a metaheuristic approach to the 2DHet-VBPP, based on Reduced variable neighborhood search (RVNS). All RVNS elements are adapted to the considered problem and many procedures are designed to improve efficiency of the method. As the Two-dimensional Homogeneous-VBPP (2DHom-VBPP) is more often treated, we considered also a special version of the RVNS algorithm to solve the 2DHom-VBPP. The results obtained and compared to both CPLEX results and results on benchmark instances from literature, justify the use of the RVNS algorithm to solve large instances of these optimization problems.

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