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A hybrid storage assignment (combination class-volume-based) framework considering quality proximity, customer and material categorization are key distinguished contents of this paper. In spite of using individual storage allocation approach, the hybrid allocation policy performs better under certain environment. The paper aims to discuss these issues.

Although it has been proved that every storage assignment policy has their advantages and limitations, one or more storage assignment policies with combination of zoning and layout design can be used together for further improvement. The authors have conducted this study at warehouse of a manufacturing firm that produce only single product with varieties of material and quality criteria. Picking optimization includes elimination of non-value-added activities like unwanted forklift and package movements, time and distance traveled for retrieval as well as storage. Other allied operations with respect to customer acceptance level and resource utilization are also considered.

The time and distance from manufacturing point to storage location are accountable as it also contributes to picking performance.

Quality-based cluster analysis is carried out to find out closeness among customers, which is used to propose algorithm with new layout design, zoning and storage allocation policy.

The purpose of this paper is to develop new model formulation for reducing the workload in pre‐batching at a manufacturer of flavors and fragrances, by optimally assigning ingredients to different storage types, taking into account past usage of ingredients and several restrictions about volumes and number of storage units.

Two models were developed, using mathematical programming, accommodating either fixed or variable shelf settings in vertical carousel storage, along with other varying storage types. The models were validated, yielding a sizeable reduction in workload, and run under varying scenarios of storage additions to reduce workload even further.

For different storage addition scenarios, application of the new model formulation yielded a reduction of 22 percent in workload. In addition, aside from space savings, approximately 40 percent of refill order total waiting time was reduced due to improved allocation.

The authors' analysis was limited by considering direct cost savings only. Yet, reduced workloads in pre‐batching may also yield indirect cost savings, such as reduced quality costs, inventory costs, and investment savings by not having to extend the pre‐batching area. Such considerations may be addressed in future research, provided data on indirect savings are available.

While intuitive storage allocation overloads the pre‐batching department and increases space utilization, suggesting an incorrect perception that more personnel and space are needed, the proposed approach provides a better alternative through optimized allocations.

The present paper adds to the literature on carousel storage location by explicitly addressing the storage sizing issue, as well as workload balancing.

Since developing efficient product-location strategies represents a critical issue in operations management, due to its impact on warehouses performance in terms of both service level and operation costs, this paper aims to focus on possible improvements in the allocation of SKUs, numerically evaluating how these can lead to a reduction of both overall required warehouse space and material handling times.

The undertaken approach focused on translating the warehouse management problem into a vertex colouring problem, modelling it as a multi-criteria problem and solving it through a properly modified algorithm.

The heuristic validation on a real industrial case demonstrated its high optimization potential, and its benchmarking simulations showed performances significantly close to the best conceivable case. Indeed, though using a dedicated storage policy, the gained optimization value turned to be definitively close to the lower bound calculated through a randomized storage policy, which, differently from the proposed solution, must be inevitably supported by a warehouse management system software.

This work presents an original multiproduct slot allocation heuristic developed by taking cue from vertex colouring problems and its pragmatic evaluation on a real industrial case; a benchmark with the randomized storage policy is also presented in order to underline the heuristic effectiveness and to point out possible future research opportunities.

The purpose of this paper is to propose a model that determines the strategy of owning and renting trucks in combinations with internal truck scheduling and storage allocation problems in container terminals.

To deal with this complicated problem, a two-level heuristic approach is developed, in which the integration problem is decomposed into two levels. The first level determines the daily operations of the internal trucks, while the second level determines the truck employment strategy based on the calculation in the first level.

The results show that: even if the using cost of owned yard trucks is much lower than the cost of rented yard tucks, terminal companies should not purchase too many trucks when the purchasing price is high. In addition, the empirical truck employment strategies, which are purchasing all the trucks or renting all the trucks, are not cost-effective when compared with the proposed yard truck employment strategy.

The paper provides a novel insight for the internal truck employment strategy in container terminals which is the determination of the strategy of employing renting and outsourcing yard trucks to meet operational daily transportation requirements and minimize the long-term cost of employing yard trucks. A mathematical model is proposed to deal with the practical problem. Also, this study presents better solution than empirical method for employing different types of yard truck. Thus, in order to obtain more benefit, terminal companies should employ the proposed yard truck employment strategy.

There is significant amount of literature tackling different issues related to the port industry. The present chapter focuses on a single business unit of seaports aiming at the documentation of works related to container terminals.

An effort to review, collect and present the majority of the works present in the last 30 years, between 1980 and 2010, has been made in order to picture the problems dealt and methods used by the authors in the specific research field. To facilitate the reader, studies have been grouped under five categories of addressed problems (productivity and competitiveness, yard and equipment utilization, equipment scheduling, berth planning, loading/unloading) and four modelling methodologies (mathematics and operations research, management and economics, simulation, stochastic modelling).

The analysis shows that most works focus on productivity and competitiveness issues followed by yard and equipment utilisation and equipment scheduling. In reference to the methodologies used managerial and economic approaches lead, followed by mathematics and operations research.

In reference to future research, two fields have been identified where there is scope of significant contribution by the academic community: container terminal security and container terminal supply chain integration.

The present chapter provides the framework for researchers in the field of port container terminals to picture the so far works in this research area and enables the identification of gaps at both research question and methodology level for further research.

To present an innovative approach to the design of a flexible order‐picking systems (OPS). The proposed conceptual framework is the first step to the development of an expert system created in a rapid and innovative manner, i.e. based on the integration of simulation, genetic algorithms and factorial analysis.

The impact of alternative policies and configurations of both picker‐to‐part and part‐to‐picker OPS is quantified, with the aim of designing and optimising robust facilities capable of minimising global costs and maximising their performances in terms of efficiency and customer service quality.

The importance of validation analysis and both virtual and on‐field data collection emerges.

Compared with the studies found in the literature, this article presents an innovative approach with original results that will be of use in the design and control of a flexible OPS.

The purpose of this paper is to represent a unique combined Real time Delphi (RTD) – analytic network process (ANP) approach considering efficient decision making with practical validation.

An ANP model encounters invisible relationship and interdependency among qualitative and quantitative criteria for assessment. RTD supports continuous assessment and improvement in team building, modeling, developing, implementing and validating the procedure. To illustrate practical validation of the model, the authors apply it in a manufacturing firm. A case illustrating the model, finds improved results and judgments followed by conclusion.

A case illustrating the model, finds improved results and judgments. This model improves warehouse performance by integrating lean and people issues. The outcome results in an efficient decision making and consensus judgments. It also fosters high trust and coordination level among people in warehouse.

Previous studies have assessed leanness either at enterprise or manufacturing level. As lean transformation and assessment both are continuous and long-term procedure, first the concept should apply to single function and should lead toward enterprise level. A web-based approach and multi criteria decision-making techniques like analytic hierarchy process, and ANP had been applied individually to measure leanness at enterprise level. Because of the warehouse contributing significantly to the total wastes and costs for an organization, such operations are considered presently.

IT was last July that we denounced the Bullock proposals because of our conviction that they would not work. True, that was not by any means the first time that we had voiced that opinion. We said so, firmly, from the moment that they were promulgated. There was so much against them.

This paper is a description of an automated overhead warehouse system, developed to store car seat covers and then to feed them to the Renault car assembly plant at Palencia (Spain). It is based on trolleys moved through monorails and stored in accumulation bars (or monorails) by gravity, having to fulfil space and shape constraints, low retrieval time requirements, etc. This paper presents the decision process and the solutions adopted in this project to overcome the constraints and to fulfil the specifications. Also, a simulation tool integrated in an object‐ oriented designing framework is presented. It has been developed to support the decision‐making process, especially at the very beginning of the project.