Designing Automated Warehouses by Minimising Investment Cost Using Genetic Algorithms

The successful performance of the automated storage and retrieval systems is dependent upon the appropriate design and optimization process. In the present work a comprehensive model of designing automated storage and retrieval system for the single- and multi-aisle systems is presented. Because of the required conditions that the automated storage and retrieval systems should be technically highly efficient and that it should be designed on reasonable expenses, the objective function represents minimum total cost. The objective function combines elements of layout, time-dependent part, the initial investment and the operational costs. Due to the nonlinear, multi-variable and discrete shape of the objective function, the method of genetic algorithms has been used for the optimization process of decision variables. The presented model prove to be very useful and flexible tool for choosing a particular type of the single- or multi aisle system in designing automated storage and retrieval systems. Computational analysis of the design model indicates the model suitability for addressing industry size problems

A Framework for the Robust Design of Unit Load Storage Systems

The unit load storage assignment problem determines the assignment of a set of unit loads with known arrival and departure times to a set of unit storage locations in a warehouse. The material handling device(s) can carry at most one unit load at the time. In this research it is assumed that each of the storage locations can be accessed directly without load relocations or rearrangements and that the travel times between the storage locations and from and to the warehousing docks can be computed in advance. The objective is to minimize the total travel time of the material handling device for performing a number of storage and retrieval operations. This type of storage system is in widespread use and implemented in both mechanized and automated systems. It is by far one of the most common storage system architectures for unit loads. The formulation of this problem belongs to the class of Assignment Problems (AP) but finding the optimal solution for the most general variant is provably hard for large problem instances. A classification of the different variants of the APs for unit loads will be presented. The size of the instance problem is proportional to the product of the number of loads and the number of locations and the number of periods in the planning horizon and is typically very large for real world problem instances. Efficient solutions algorithms only exist for product-based storage policies or for the very special case of a perfectly balanced warehouse for load-based storage policies. However, for load-based storage policies the integrality property is not satisfied in general. This results in very large binary programming problems that to date cannot be solved to optimality. However, the formulations have special structure that can be exploited to design efficient solution algorithms. Properties and the special structure of the formulation will be presented. A specialized compound solution algorithm combines primal and dual approaches and heuristics to reduce the optimality gap. Initial computational experience will be shared. It is anticipated that the solution algorithm can either be directly implemented in commercial warehouse management systems or that it becomes a tool to evaluate the performance of commercially implemented storage policies. The above formulation is the sub problem in a decomposition algorithm for the design of unit load storage systems that identifies the tradeoffs between efficiency and risk of the performance of the storage system. Different risk measures such as the standard deviation and the downside risk can be used. An example based on realistic data values shows that in this case operator-controlled systems are less expensive and more risky than automated systems. However, if the same level of risk is mandated then the automated system is less expensive

Sequencing approaches for multiple-aisle automated storage and retrieval systems

Automated storage and retrieval systems (AS/RS) are used in high velocity distribution centres to provide accurate and fast order processing. While almost every industrial system is comprised of many aisles, most of the academic research on the operational aspects of AS/RS is devoted to single-aisle systems, probably due to the broadly accepted hypothesis proposing that an m aisles system can be modelled as m 1-aisle independent systems. In this article, we present two multi-aisles sequencing approaches and evaluate their performance when all the aisles are managed independently first, and then in a global manner. Computational experiments conducted on a multi-aisle AS/RS simulation model clearly demonstrate that a multi-aisle system cannot be accurately represented by multiple single-aisle systems. The numerical results demonstrate that, when dealing with random storage, globally sequencing multi-aisle AS/RS leads to makespan reductions ranging from 14 to 29% for 2- and 3-aisle systems, respectivelyKeywords: automated storage and retrieval systems; multi-aisle; sequencing; simulatio

Design of automaded storage and retrieval systems in pharmaceutical industry

U radu su predstavljene neke osnovne smernice za projektovanje automatskih skladišta u farmaceutskoj industriji: vrsteskladištenog materijala, uslovi čuvanja materijala, osnovne karakteristike podsistema za prijem materijala, osnovne karakteristike podsistema za komisioniranje i zahtevani ambijentalni uslovi. Predstavljen je analitički model za određivanje očekivanih vremena ciklusa dizalice kod automatskih skladišta opsluživanih dizalicama sa regalima dvostruke dubine, budući da je ovo, verovatno, najčešće korišćena tehnologija skladištenja u podsistemu glavnog skladišta u farmaceutskim fabrikama. Usled izuzetne važnosti ispunjenja savremenih zahteva za distribucijom malih, frekventnih porudžbina, predstavljeni su analitički modeli za određivanje očekivanih vremena ciklusa kod automatskih skladišta za male terete opsluživanih dizalicama i automatskih skladišta za male terete opsluživanih skladišnim vozilima, koja definišu protok transportnih jedinica kroz sistem. Svi navedeni modeli mogu poslužiti projektantima i inženjerima koji se ovim problemima bave u praksi, kao i proizvođačima ovih sistema, da odrede meru uspešnosti projektnih rešenja, odnosno, da garantuju potencijalnim korisnicima najvažnije performanse sistema.The paper addresses some basic guidelines for the automated storage and retrieval systems design in pharmaceutical industry: types of pharmaceutical materials, materials storage keeping conditions, receiving subsystem main characteristics, order picking subsystem main characteristics and requested environment conditions. Analytical travel time model for the estimation of cycle times for the unit-load double-deep automated storage and retrieval systems is presented as it is the most common automated storage and retrieval systems type in main warehouse subsystem in pharmaceutical industry. Due to the great importance of very frequent small orders distribution in oday's logistic, analytical travel time model for the computation of travel cycle times for mini-load multi-shuttle automated storage and retrieval system and shuttle based storage and retrieval systems are presented. All models could help designers, professionals in practice even a producers of these systems to estimate successions of offered solutions or to guarantee most important system performance achievement

Multi-objective optimisation model of shuttle-based storage and retrieval system

This paper presents a multi-objective optimisation solution procedure for the design of the Shuttle-Based Storage and Retrieval System (SBS/RS). An efficient SBS/RS design should take into account multi-objectives for optimization. In this study, we considered three objective functions in the design concept which are the minimization of average cycle time of transactions (average throughput time), amount of energy (electricity) consumption and total investment cost. By also considering the amount of energy consumption as an objective function for minimization, we aimed to contribute to an environmentally friendly design concept. During the optimization procedure, we considered seven design variables as number of aisles, number of tiers, number of columns, velocities of shuttle carriers, acceleration/deceleration of shuttle carriers, velocity of the elevators lifting tables and acceleration/deceleration of the elevators lifting tables. Due to the non-linear property of the objective function, we utilized the Non-Dominated Sorting Genetic Algorithm II (NSGA II) genetic algorithm for facilitating the solution. Lastly, we searched Pareto optimal solutions to find out the optimum results. We believe that this study provides a useful and a flexible tool for warehouse planners and designers, while choosing a particular type of SBS/RS at the early stage of the warehouse design. First published online: 12 May 201

Otomatik depolama ve geri-alma sistemlerinin simülasyon ile performans analizi

Otomatik depolama ve geri-alma sistemleri, hem üretim hem dağıtım ortamlarında, ürünlerin depolanması ve geri-alınması için yaygın bir şekilde kullanılan sistemlerdir. Bu sistemlerin birçok avantajının yanında yüksek başlangıç yatırımları ve depo tasarımının değiştirilmesinin zorluğu gibi ekonomik faktörleri içeren dezavantajlarının da bulunması, sistemin fiziksel tasarım ve kontrol parametrelerinin doğru bir şekilde belirlenmesi gerekliliğini ön plana çıkarmaktadır. Dolayısıyla, sistem kurulmadan önce ya da kurulduktan sonra sistemin performans analizlerinin yapılması optimal bir tasarımın gerçekleştirilmesi açısından önem kazanmaktadır. Bununla birlikte, otomatik depolama ve geri-alma sistemlerinin tasarımında fiziksel tasarım ve kontrol parametrelerinin eş zamanlı olarak ele alınması karmaşık bir optimizasyon probleminin ortaya çıkmasına neden olduğundan, problemin çözümünde farklı parametre kombinasyonlarını içerecek şekilde bir tasarım esnekliği sağlanmak istenmektedir. Bu da, problemin çözümü için en uygun yaklaşımlardan birinin simülasyon olduğunu göstermektedir. Bu çalışmada, otomatik depolama ve geri-alma sistemlerinin simülasyonu ele alınmış olup, simülasyon modelinin oluşturulması için bir yaklaşım önerilmektedir. Önerilen yaklaşımın örneklendirilmesi amacıyla örnek bir depo oluşturulmuştur. Çalışma kapsamında, farklı depo içi atama politikaları altında farklı depolama ve geri-alma makinesi bekleme noktası parametreleri dikkate alınmıştır. Çeşitli senaryolar ile ilgili parametrelerin sistem üzerindeki etkisinin incelenmesi amaçlanarak, elde edilen sonuçlar sistem performansı açısından değerlendirilmiştir.Automated storage and retrieval systems are widely used in both production and distribution environments for the storage and retrieval of products. Besides the many advantages of these systems, the disadvantages (which include economic factors such as high initial investments and the difficulty of changing the warehouse design) highlights the need to correctly determine the system’s physical design and control parameters. In order to achieve an optimal design, it is therefore important to conduct a performance analysis of the system before or after installation. Dealing simultaneously with physical design and control parameters when designing automated storage and retrieval systems is, however, quite a complex undertaking whose solution requires the development of a flexible design incorporating several combinations of parameters. These considerations make the simulation approach the most appropriate means of solving the problem. The current study focuses on automated storage and retrieval systems, and proposes an approach for developing a simulation model. A sample warehouse is designed in order to illustrate the proposed approach. The study examines a variety of dwell point parameters of the storage and retrieval machine under different storage assignment policies. The findings obtained are finally evaluated with respect to the system’s performance in order to measure the impact of those parameters that are related to a variety of scenarios in the system

Collaboration modes and advantages in supply chain

This research aims to address supply chain collaboration with a perspective of broader three-dimensional relationship, not a linear two-dimensional relationship discussed broadly in previous research. Case study was adopted for this research, and data collection was mainly conducted via interview. The research results highlighted that supply chain collaborations are common practice across all levels of the pharmaceutical supply chain. The results also indicated that the different strengthen levels of barging power among collaborative partners will influence the achieved advantages at different supply chain levels, including strategic, operational and political levels

Smart manufacturing and supply chain management

In the fourth industrial revolution, smart manufacturing will be characterized by adaptability, resource efficiency and ergonomics as well as the integration of customers and business partners in business and value processes. Business model, operations management, workforce and manufacturing process all face substantial transformations to reasoning the manufacturing process. This paper explores the impacts of smart manufacturing on supply chain management, and develops several propositions to improve supply chain performance under the context of smart manufacturing

Analytical travel time models for multi aisle automated storage and retrieval systems

Multi aisle automated storage and retrieval systems correspond to multiple picking aisles served by a single storage and retrieval machine. These systemsare used in practice when the need for pallet places is high and the throughput capacity is relatively low. Therefore, considerable savings of initial investment costs due to single aisle systems can be achieved using such systems. The objective of the presented study is to develop analytical travel time models for multi aisle automated storage and retrieval systems considering the operating characteristics of the storage and retrieval machine. With the proposed analytical travel time models, average travel time of the storage and retrieval machine, from which the performance of multi aisle automated storage and retrieval systems can be evaluated is determined. A simulation model of multi aisle automated storage and retrieval systems was developed to compare the performances of the proposed analytical travel time models. An example of multi aisle automated storage and retrieval systems withfive picking aisles was presented for the evaluation purpose. The results show that proposed analytical travel time models perform satisfactory according to the results of simulation analysis and could be very useful toolsfor designing of multi aisle automated storage and retrieval systems in real-world applications