Heungsoon Felix Lee

Sequencing methods for automated storage and retrieval systems with dedicated storage

In this paper, we study the effect of sequencing storage and retrieval requests on the performance of automated storage and retrieval systems (AS/RS) where a storage request is assigned a predetermined storage location. By exploiting this unique operating characteristic, we present several optimum and heuristic sequencing methods under static and dynamic approaches. Applications of such sequencing methods include unit-load AS/RS with dedicated storage, miniload AS/RS, and potentially unit-load AS/RS with randomized storage. We find that the sequencing methods can significantly reduce travel time by a storage and retrieval machine, thereby, increasing throughput, and that the dynamic heuristic method is simple and fast, yet considerably outperforms the others.

Retrieval sequencing for unit-load automated storage and retrieval systems with multiple openings

Automated storage and retrieval systems (AS/RS) have made a dramatic impact on material handling and inventory control in warehouses and product systems. A unit-load AS/RS is generic and other AS/RS represent its variations. In this paper, we study a problem of sequencing retrieval requests in a unit-load AS/RS. In a unit-load AS/RS, there are usually multiple openings and a unit-load can be stored in any opening. Given a list of retrieval requests and the locations of openings, this problem seeks a sequence of dual cycles that minimizes total travel time taken by a storage/retrieval machine. Previous researchers believed that this problem is computationally intractable and provided greedy-style heuristic algorithms. In this paper, we present an algorithm that combines the Hungarian method and the ranking algorithm for the assignment problem with tour-checking and tour-breaking algorithms. We show that this algorithm finds either a verified optimal or near-optimal solution quickly for moderate size proble...

Performance analysis for automated storage and retrieval systems

Abstract Automated storage and retrieval (AS/R) systems have had a dramatic impact on material handling and inventory control in warehouses and production systems. A unit-load AS/R system is generic and other AS/R systems represent its variations. Common techniques that are used to predict performance of a unit-load AS/RS are a static analysis or computer simulation. A static analysis requires guessing a ratio of single cycles to dual cycles, which can lead to poor prediction. Computer simulation can be time-consuming and expensive. In order to resolve these weaknesses of both techniques, we present a stochastic analysis of a unit-load AS/RS by using a single-server queueing model with unique features. To our knowledge, this is the first study of a stochastic analysis of unit-load AS/R systems by an analytical method. Experimental results show that the proposed method is robust against violation of the underlying assumptions and is effective for both short-term and long-term planning of AS/R systems.

A Line-Balancing Strategy for Designing Flexible Assembly Systems

We present a rough-cut analysis tool that quickly determines a few potential cost-effective designs at the initial design stage of flexible assembly systems (FASs) prior to a detailed analysis such as simulation. It uses quantitative methods for selecting and configuring the components of an FAS suitable for medium to high volumes of several similar products. The system is organized as a series of assembly stations linked with an automated material-handling system moving parts in a unidirectional flow. Each station consists of a single machine or of identical parallel machines. The methods exploit the ability of flexible hardware to switch almost instantaneously from product to product. Our approach is particularly suitable where the product mix is expected to be stable, since we combine the hardware-configuration phase with the task-allocation phase.For the required volume of products, we use integer programming to select the number of stations and the number of machines at each station and to allocate tasks to stations. We use queueing network analysis, which takes into account the mean and variance of processing times among different products to determine the necessary capacity of the material-handling system. We iterate between the two analyses to find the combined solution with the lowest costs. Work-in-process costs are also included in the analysis. Computational results are presented.

An Integrated design support method for flexible assembly systems

Abstract Existing design aids for flexible assembly systems (FASs) have had limited success in real applications because of the simplicity of the underlying assumptions, treatment of isolated design issues, time-consuming techniques, lack of user-friendly design-aid tools, and no machine flexibility consideration. The proposed integrated design support system takes three basic data (products, potential machines, and material handling systems) as input and provides (1) cost-effective flow system designs (layouts and operating policies) that satisfy design and production requirements and (2) economic assessment for the investment plan. The three phases of the system—rough-cut analysis, detailed analysis, and investment plan analysis—encompass queuing networks, optimization methods, discrete-event computer simulation, and engineering economy. The system is the first truly integrated method to support design activities and economic justification for FASs. A case study shows the proposed systems effectiveness and efficiency.

The optimal configuration and workload allocation problem in flexible manufacturing systems

In this article we consider the problem of determining the minimum cost configuration (number of machines and pallets) for a flexible manufacturing system with the constraint of meeting a prespecified throughput, while simultaneously allocating the total workload among the machines (or groups of machines). Our procedure allows consideration of upper and lower bounds on the workload at each machine group. These bounds arise as a consequence of precedence constraints among the various operations and/or limitations on the number or combinations of operations that can be assigned to a machine because of constraints on tool slots or the space required to store assembly components. Earlier work on problems of this nature assumes that the workload allocation is given. For the single-machine-type problem we develop an efficient implicit enumeration procedure that uses fathoming rules to eliminate dominated configurations, and we present computational results. We discuss how this procedure can be used as a building block in solving the problem with multiple machine types.

Algorithms for the constrained maximum-weight connected graph problem

Given a positive integer R and a weight for each vertex in a graph, the maximum-weight connected graph (MCG) problem is to find a connected subgraph with R vertices that maximizes the sum of the weights. The MCG problem is strongly NP-complete, and we study a special case of it: the constrained MCG (CMCG) problem, which is the MCG problem with a constraint of having a predetermined vertex included in the solution. We first show that the Steiner tree problem is a special case of the CMCG problem. Then we present three optimization algorithms for the CMCG problem. The first two algorithms deal with special graphs (tree and layered graphs) and employ different dynamic programming techniques, solving the CMCG problem in polynomial times. The third one deals with a general graph and uses a variant of the Balas additive method with an imbedded connectivity test and a pruning method. We also present a heuristic algorithm for the CMCG problem with a general graph and its bound analysis. We combine the two algorithms, heuristic and optimization, and present a practical solution method to the CMCG problem. Computational results are reported and future research issues are discussed.

Strategic allocation of inspection stations for a flow assembly line : a hybrid procedure

A hybrid method is presented for the design of inspection stations in serial production systems. The hybrid method combines a constrained bottleneck shortest path algorithm and discrete event simulation. The network method determines the allocation of the inspection stations and the simulation helps the decision maker estimate accurately the possible outcome of the allocation. A computational study with the method is performed based on a practical problem. Other aspects related to the application of the method to real problems are also discussed.

Characteristics of optimal workload allocation for closed queueing networks

Abstract We consider the problem of allocating a given workload among the stations in a multi-server product-form closed queueing network to maximize the throughput. We first investigate properties of the throughput function and prove that it is pseudoconcave for some special cases. Some other characteristics of the optimal workload and its physical interpretation are also provided. We then develop two computational procedures to find the optimum workload allocation under the assumption that the throughput function is pseudoconcave in general. The primary advantage of assuming pseudoconcavity is that, under this assumption, satisfaction of first order necessary conditions is sufficient for optimality. Computational experience with these algorithms provides additional support for the validity of this assumption. Finally, we generalize the solution procedure to accommodate bounds on the workloads at each station.

A shift-based sequencing method for twin-shuttle automated storage and retrieval systems

The continuing need for high-throughput Automated Storage and Retrieval Systems (AS/RS) has lead to the introduction of storage/retrieval machines that can carry more than one unit-load. However, this technology involves a large capital investment so careful operating methods are desired to make the most of its capabilities. In this paper, we study a shift-based sequencing problem for twin-shuttle AS/RS, where depletion (retrieval operations) and replenishment (storage operations) of items occur over different shifts. For example, certain warehouses or distribution depots deplete their items in stock during morning shifts and replenish during later shifts. We show that this problem can be transformed into the minimum-cost perfect matching problem and present an efficient polynomial-time optimum method that can achieve a large throughput gain over other methods. We also provide average-case and lower bound analyses for this problem.