A branch and bound algorithm for class based storage location assignment

Class-based storage implementation decisions have significant impact on the required storage space and the material handling cost in a warehouse. In this paper, a nonlinear integer programming model is proposed to capture the above. Effects of storage area reduction on order picking and storage space cost are incorporated. A branch and bound algorithm is developed to solve the model. Computational experience with randomly generated data sets and an industrial case shows that branch and bound algorithm is computationally more efficient than a baseline dynamic programming algorithm. It is further observed that the class based policy results in lower total cost of order picking and storage space than the dedicated policy. (C) 200

Class-based storage-location assignment to minimise pick travel distance

Storage-location assignment in warehouses is an important task as it impacts productivity of other warehouse processes. The class-based storage policy distributes the products, among a number of classes, and for each class it reserves a region within the storage area. We propose a nonlinear integer-programming model to the problem of formation of classes and allocation of storage space, considering savings in required storage space, due to random allocation of products within a class. We develop a branch and bound algorithm (BBA) to solve the model and compare it with a benchmark dynamic programming algorithm (DPA). These algorithms are applied to randomly generated data sets and to an industrial case. Computational experience shows that class-based policy can result in shorter pick-travel distances than the dedicated policy. The proposed BBA is found to be computationally much more efficient than DPA

Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

Class-based storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. The procedures reported in the literature for formation of storage classes primarily consider order-picking cost ignoring storage-space cost. Moreover, in these procedures items are ordered on the basis of their cube per order index (COI), and items are then partitioned into classes maintaining this ordering. This excludes many possible product combinations in forming classes which may result in inferior solutions. In this paper, a simulated annealing algorithm (SAA) is developed to solve an integer programming model for class formation and storage assignment that considers all possible product combinations, storage-space cost and order-picking cost. Computational experience on randomly generated data sets and an industrial case shows that SAA gives superior results than the benchmark dynamic programming algorithm for class formation with COI ordering restriction. (c) 200

The use of recursive ABC method for warehouse management

The paper solves complex warehouse simulation to achieve effective solution. Most attention is focused on the use of recursive ABC method for warehouse management. The aim of the simulation study is to verify whether recursive ABC method yield additional benefits in optimizing the warehouse. The complete simulation and the mathematical calculations are performed in the Witness Lanner simulation tool. The aim of this simulation study is to discover a better solution using recursive ABC method in each part of the model. The basic warehouse is based on the ABC method. Further, the simulation study provides recommendations that can improve warehouse management and thus reduce costs. The Witness simulation environment is used for modeling and experimenting. All mathematical calculations and simulations are evaluated and measured, as well as all settings of input and output values. Description of the proposed simulation experiments and evaluation of achieved results are presented. © 2019, Springer Nature Switzerland AG.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Program [LO1303 (MSMT-7778/2014)]; European Regional Development Fund, under CEBIA-Tech ProjectEuropean Union (EU) [CZ.1.05/2.1.00/03.0089

The simulation study of recursive ABC method for warehouse management

The paper deals with a complex warehouse simulation to accomplish a competent solution. It belongs to a group of articles where we are constantly trying to explore the use of warehouses and add further extensions. Greater consideration is concentrated on the use of recursive ABC method for warehouse management in extended concept. The aspiration of the simulation study is to prove whether recursive ABC method returns additional benefits in optimizing the warehouse in this case at a warehouse of different sizes. The complete simulation and the mathematical calculations are accomplished in the Witness Lanner simulation program. The goal of this simulation study is to observe a better solution using recursive ABC method in each part of the model multiple times. Both warehouses are established first on the ABC method, secondary are based on the recursion method. The focus is on two very different layouts of warehouses. Further, the simulation study contributes to propositions that can enhance warehouse management and thus decrease costs. The Witness simulation environment is used for modelling and experimenting. All mathematical computations and simulations are evaluated and measured, as well as all settings of input and output values. Description of the proposed simulation experiments and evaluation of achieved results are presented in tables. © 2019, Springer Nature Switzerland AG.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT7778/2014)]; European Regional Development Fund under the project CEBIATech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/FAI/2017/003