Efficiency Of Warehouse Research Articles

Multi-objective AGV scheduling in an automatic sorting system of an unmanned (intelligent) warehouse by using two adaptive genetic algorithms and a multi-adaptive genetic algorithm.

Automated guided vehicle (AGV) is a logistics transport vehicle with high safety performance and excellent availability, which can genuinely achieve unmanned operation. The use of AGV in intelligent warehouses or unmanned warehouses for sorting can improve the efficiency of warehouses and enhance the competitiveness of enterprises. In this paper, a multi-objective mathematical model was developed and integrated with two adaptive genetic algorithms (AGA) and a multi-adaptive genetic algorithm (MAGA) to optimize the task scheduling of AGVs by taking the charging task and the changeable speed of the AGV into consideration to minimize makespan, the number of AGVs used, and the amount of electricity consumption. The numerical experiments showed that MAGA is the best of the three algorithms. The value of objectives before and after optimization changed by about 30%, which proved the rationality and validity of the model and MAGA.

PENERAPAN WAREHOUSE MANAGEMENT SYSTEM PADA PT UNIPLASTINDO INTERBUANA BALI

Warehouse Management System is a database-based computer application system, which used to improve warehouse efficiency in maintaining the accuracy of inventory data by recording every transaction in the warehouse. The purpose of this study was to determine efficiency of material handling costs incurred after implementation of warehouse management system. The research was conducted at PT Uniplastindo Interbuana Bali with simulation of implementation warehouse management system. Based on calculations, application of WMS able to increase cost efficiency and time efficiency in material handling because the system is able to provide accurate material placement data. Data during simulation shows a smaller amount of time compared to before simulation, which means less costs are incurred. Existence of system also makes it easy for related admin to collect data on real stock in the field. Data presentation and processing becomes faster and accurate so it can lead to increased performance in company.
 Keywords: Warehouse Management System (WMS), material handling, cost efficiency 

Optimal Storage Locations for Warehouse Efficiency Improvement in a Haircare Manufacturer

Optimal Storage Locations for Warehouse Efficiency Improvement in a Haircare Manufacturer

Study of an innovative method based on complementarity between ARIZ, lean management and discrete event simulation for solving warehousing problems

Warehousing challenges require not only effective management but also a new innovative strategy that can significantly improve warehouse efficiency. This study presents an innovative method for solving warehouse problems and achieving low-cost warehousing, based on complementarities between ARIZ (Algorithm for Inventive Problem Solving), lean warehousing approach and discrete event simulation. In the proposed model, the lean warehousing is first used to understand and analyze problems in order to propose solutions that improve warehouse system efficiency. Then, a model of the improved system is developed and analyzed in a predictive simulation software (Witness1https://www.lanner.com/en-gb/technology/witness-simulation-software.html.1), to evaluate its performance. The discrete event simulation allows for experiments on the system to be created and analyzed. Thus, an experimental design was developed to establish the cause-and-effect relationships between the parameters of the system in order to formulate a generalized system of contradictions. And finally, ARIZ is used to address related contradictions for searching for an innovative solution, which must be subsequently implemented and evaluated in the discrete event simulation. The applicability of the proposed method is demonstrated through a case study, involving an automotive company specialized in the manufacturing of electronic modules that wants to reduce raw material warehousing costs. Generally, the aim of the proposed method, which combined lean management, discrete event simulation and the ARIZ algorithm, is to be able to propose solutions that go beyond the limits of continuous improvement and optimization methods. Such an approach enables to propose a kind of continuum between traditional multi-objectives methods and inventive ones.

How to optimize storage classes in a unit-load warehouse

Abstract We study a problem of optimizing storage classes in a unit-load warehouse such that the total travel cost is minimized. This is crucial to the operational efficiency of unit-load warehouses, which constitute a critical part of a supply chain. We propose a novel approach called the FB method to solve the problem. The FB method is suitable for general receiving-dock and shipping-dock locations that may not coincide. The FB method first ranks the locations according to the frequencies that they are visited, which are estimated by a linear program based on the warehouse’s layout as well as the products’ arrivals and demands. The method then sequentially groups the locations into a number of classes that is implementable in practice. After forming the classes, we use a policy based on robust optimization to determine the storage and retrieval decisions. We compare the robust policy with the traditional storage-retrieval policies on their respective optimized classes. Our results suggest that if the warehouse utilization is low, different class-formation methods may lead to very different total travel costs, with our approach being the most efficient. We observe the robustness of this result across various parameter settings. A case study based on data from a third-party logistics provider suggests that the robust policy under the FB method outperforms the other storage-retrieval policies by at least 8% on average, which indicates the potential savings by our approach in practice. One of our findings is that the importance of optimizing classes depends on the warehouse utilization.

Genetic algorithms applied to integration and optimization of billing and picking processes

This article intends to provide a computational tool that integrates and provides optimized solutions to two interdependent problems called Optimized Billing Sequencing (OBS) and Optimized Picking Sequence (OPS). These problems are addressed separately by the existing literature and refer respectively to the optimization of billing and picking processes in a typical warehouse with low-level picker-to-parts system. Integration literature is, therefore, limited and there is a demand for more robust OBS/OPS optimization methods. This approach will deal with practical dilemmas that have not been addressed by researchers yet to propose an extension to the OBS model by Pinto et al. (J Intell Manuf 29(2):405–422, 2018) along with a specific variation of the Order Batching and Sequencing Problem. The premise is to prove to managers the possibility of making more consistent decisions about the trade-off between the level of customer service and the warehouse efficiency. The proposed tool is formulated by the integration of two Genetic Algorithms called GA-OBS and GA-OPS where GA-OBS maximizes the order portfolio billing and generates the picking order to the OPS, whereas GA-OPS comprises the iteration of batch and routing algorithms to minimize picking total time and cost to the OPS. Experiments with problems with different complexity levels showed that the proposed tool produces solutions of satisfactory quality to OBS/OPS. The approach proposed fills a gap in the literature and makes innovative contributions to the development of more suitable optimization methods to the reality of warehouses.

Implications of Goods and Services Tax reform on the Make in India initiative: A system dynamics perspective

AbstractThe paper highlights the implications of Goods and Services Tax (GST), a major tax reform in India launched in July 2017 on the Make in India initiative launched in the year 2014. The GST is expected to trigger its impact on the following eight elements: warehouse efficiency, interstate check‐post operations, informal to formal business transition, interstate business expansion by micro, small, and medium enterprises, simplicity and transparency in tax collection process, logistics cost reductions, ease of doing business in India, and working capital cost realignment, which in turn may accelerate the manufacturing growth in Indian economy. In order to study the impact of the factors of GST on the Make in India initiative and the manufacturing growth, a system dynamics approach has been adopted in this paper. A number of simulation runs carried out using the system dynamics modelling have provided meaningful insights to the policymakers and strategic planners for evolving strategies for manufacturing growth.

Advanced allocation policy in class-based storage to improve AS/RS efficiency toward green manufacturing

Warehouse storage spaces assignment to items method almost effect on all key characteristics of warehouse efficiency. Cube-per-order index defines as the ratio of required space for storing each item to the number of its retrieval and demand request. In order to introduce some new impressing parameters for items layout in class-based storage, we tried to present a new index rather than before to encompass mentioned cases. Our multi-objective optimization problem model develops an allocation and product layout model in a class-based storage which applies an automatic storage and retrieval system (AS/RS) with considering energy consumption optimization and energy sustainability. Also, with adding the second objective to our model, we minimized energy costs while allocating items to locations with the minimum movement priority in AS/RS. Related model will be developed through decreasing electricity in allocation, optimum movement and consequently with helping to energy sustainability and reaching to sustainable manufacturing. In summary, with introducing the proposed model, recognizing affecting factors on mentioned index, applying analytical hierarchy process and incorporating experts opinions, we create this new index and examine the consistency of matrix (which weights are acquired from it) to determine the weight of each upon impressing criteria in allocation. Next, we run our developed model using Lingo software and by applying five multi-objective optimization techniques.

An Evaluation of Picking Routing Policies to Improve Warehouse Efficiency

An Evaluation of Picking Routing Policies to Improve Warehouse Efficiency

Flexural behaviour of steel storage rack beam-to-upright bolted connections

Steel storage pallet racks are usually unbraced in the down-aisle direction in order to make palletised goods always accessible. The down-aisle stability of unbraced rack structures mainly depends on the performance of beam-to-upright connections and column bases. Beam-to-upright boltless connections are commonly employed for their convenience in assembly and adjustment. Since storage racks are being designed to considerable heights for the purpose of improving warehouse efficiency, steel storage rack beam-to-upright bolted connections are gradually being introduced to improve the structural stability. The paper presents an experimental investigation into the flexural behaviour of beam-to-upright bolted connections of steel storage pallet racks. A total of twenty-one specimens were tested under monotonic loading in a single cantilever test setup, including three different size pallet beams, three different upright thicknesses, and beam-end-connectors with two or three tabs. This study examines deformation patterns and failure modes of the connections, their rotational stiffness, moment resistance and corresponding connection rotations. The results show that steel storage rack beam-to-upright bolted connections, classified as “semi-rigid” and “partial-strength” connections, generally experience ductile failure modes. The effects of critical geometric parameters, i.e. upright thickness, beam height and the number of tabs, on the flexural behaviour of bolted connections are also investigated. In addition, comparisons of performance and failure modes between bolted and boltless connections are made. Moreover, in order to promote the design by advanced analysis of rack structures, a preliminary theoretical model based on the Component Method is proposed to predict the initial rotational stiffness of beam-to-upright bolted connections in steel storage pallet racks. A good agreement is obtained between the initial rotational stiffness derived from the theoretical model and the experimental tests.

Warehouse efficiency improvement using RFID in a humanitarian supply chain: Implications for Indian food security system

This paper investigates the impact of RFID adoption in a non-profit supply chain scenario to study the effect of available rate of ordering and shrinkage recovery rate on overall costs at the warehouse level. We model the situation as a Newsvendor problem with the objective to minimize the total expected cost and compare two scenarios with and without RFID for managing the inventory subjected to shrinkage and misplacement. We apply the model to Indian food security system and the results show that, incentive to deploy RFID depends on the deprivation cost, the severity of error and the shrinkage recovery rate.

Augmented Reality in Warehouse Operations: Opportunities and Barriers

In today’s business environment, the efficiency of warehouses can be critical for the efficiency of the overall supply chains they belong to. As a result, new technologies are being tested and adopted in industry to improve the performance of warehouse operations. An example technology that has recently gained interest by both academia and industry is augmented reality. In this paper, we investigate the opportunities arising from the usage of augmented reality in warehouses as well as the barriers for its industrial adoption. This is done via a series of practitioners interviews and via an experiment designed using Google Glass. Our results indicate that even though the technology is not mature enough at the moment, the potential benefits it can offer make it promising for the near future.

Increasing the energy efficiency of warehouses using demand-side management mechanisms

The complex approach and expansion of the functionality of DSM programs is offered due to the application of services and criteria for classification of warehouses in terms of energy efficiency. When analyzing the effectiveness of the application of DSM programs, namely the optimality of power consumption modes, it is suggested to assess the power supply mode during the entire technological period. Considering the electrical supply of warehouses as an electricity supply to the consumer with sharply variable nonlinear characteristics, the power of which is supplied from the generators, the operating voltage and current values of which are variable, it is proposed to use the modified Frieze inactive power index. The use of the Q F index is advisable, since it will be located even in the absence of reactive elements in the consumer system. The influence of the consumption mode on the first harmonic is analyzed. The received characteristics are caused by presence of influence of consumption mode on the general characteristics of electricity supply mode optimality. The analysis of higher harmonics can also be used to assess the effect of unevenness. Such analysis requires additional studies, but it can be argued that the use of the Frieze inactive power index allows to assess the degree of uneven electricity consumption in accordance with a given optimal level.

Application of Dynamic Value Stream Mapping in Warehousing Context

Uncertainty within supply chains increases the risk of not meeting objectives. Warehouses can absorb some of these uncertainties, by accumulating inventory. This accumulation has led many to consider warehouses as a source of waste in supply chains. Hence, there is limited research that seeks improving intrinsic warehouse efficiency; particularly in the context of Lean concepts and Value Stream Mapping (VSM). Since, warehouses seek to absorb uncertainty in supply chain by holding inventory; this uncertainty absorption may introduce variability to warehousing function itself. Therefore a methodology is required, which can capture the embodied dynamic within warehousing function. This paper reflects Lean concepts and, in particular, VSM to warehousing context and introduces some methods and guidelines to assure the proper application of VSM in what is an uncertain and dynamic system. In this paper, warehousing function is formulated based on some abstract processes which vary on their output status. This formulation facilitates identifying value-adding activities as one of the most substantial steps, yet confusing in application of VSM in warehousing context. The suggested methods enable fundamental statistical/mathematical analysis, which leverage VSM to a more dynamic evaluation tool. Application of the introduced approach will facilitate the decision making process for warehouse systems evaluation and improvement. The resultant methodology is applied to a factual case and this serves to demonstrate its practical application. It is worth mentioning that the findings applications, which can be termed ‘dynamic VSM’, are not limited to warehouses but can also be applied to any dynamic environment with non-deterministic processes.

Managing warehouse efficiency and worker discomfort through enhanced storage assignment decisions

Humans are at the heart of crucial processes in warehouses. Besides the common economic goal of minimising cycle times, we therefore add in this paper the human well-being goal of minimising workers’ discomfort in the context of order picking. We propose a methodology for identifying the most suitable storage location solutions with respect to both goals. The first step in our methodology is to build data-driven empirical models for estimating cycle times and workers’ discomfort. The second step of the methodology entails the use of these empirically grounded models to formulate a bi-objective assignment problem for assigning products to storage locations. The developed methodology is subsequently tested on two actual warehouses. The results of these practical tests show that clear trade-offs exist and that optimising only for discomfort can be costly in terms of cycle time. Based on the results, we provide practical guidelines for taking storage assignment decisions that simultaneously address discomfort and travel distance considerations.

Logistics network optimization considering balanced allocation and vehicle routing

This article presents an effort to study the complex problem that arises when balanced allocation is integrated with vehicle routing decisions in a logistics network. This integrated problem is frequently encountered in many logistics networks that maximize the efficiency and effectiveness of available warehouses and distribution centers. After modeling the balanced allocation vehicle routing problem (BAVRP) as a multi-objective mixed integer programming problem, we propose a two-stage approach as a solution methodology. This approach decomposes the BAVRP into two independent sub-problems, allocation and routing, and solves them separately. Experimental results show that our two-stage algorithm approach is readily applicable to the BAVRP.

Genetic Scheduling and Reinforcement Learning in Multirobot Systems for Intelligent Warehouses

A new hybrid solution is presented to improve the efficiency of intelligent warehouses with multirobot systems, where the genetic algorithm (GA) based task scheduling is combined with reinforcement learning (RL) based path planning for mobile robots. Reinforcement learning is an effective approach to search for a collision-free path in unknown dynamic environments. Genetic algorithm is a simple but splendid evolutionary search method that provides very good solutions for task allocation. In order to achieve higher efficiency of the intelligent warehouse system, we design a new solution by combining these two techniques and provide an effective and alternative way compared with other state-of-the-art methods. Simulation results demonstrate the effectiveness of the proposed approach regarding the optimization of travel time and overall efficiency of the intelligent warehouse system.

Study on Dynamic Slotting Optimization in Storage System

In order to improve the efficiency of warehouse on picking, an optimal model for ware location assignment is presented, which is with multi-objective function. To solve the multi-objective optimization problem, a differential evolution algorithm combined with lexicographic sort algorithm is presented. In order to verify the above algorithm, an example is presented. The calculated results show that the algorithm is operable and versatile. The optimized solution can be found fast with better fitness than genetic algorithm which is used to be compared.

The Optimization of Slotting Based on the Power Drive-Through Rack

Logistics has become "the third profit source", we do the optimization research of storage system based on the power drive-through rack designed by our research group. According to the optimization model and using the Multi-Objective Genetic Algorithms, we take a logistics distribution center as an example. Introduct of cargo weight, quantity and warehousing frequency parameters, mimicing the process of natural selection, mutation and evolution in biological world, following the survival of the fittest mechanism, obtain the distribution of cargo space in Power drive-through Rack. High weight goods is in bottom shelves, making the center of goods gravity more lower. High quantity and frequency goods is near the entrances of warehouse; making the distribution become more reasonable. Improve the efficiency and utilization of warehouse.

Route Optimization of Stacker in Automatic Warehouse Based on Genetic Algorithm

Today, automatic warehouse system gradually replaced manual labor, and played an important role in the production work, especially in the cargo handling work. It was important to research the time-consuming and efficiency of stacker in the automated warehouse system. This paper researched the path of stacker in automated warehouse and calculated the operation time of stacker working path according to actual working condition, and then put forward a route optimization method of stacker based on genetic algorithm, finally simulated this algorithm by using MATLAB. The simulation results showed that this algorithm could shorten the way of stacker, and increase the working efficiency of the warehouse. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.2959