Operations and Supply Chain Managementhttp://hdl.handle.net/10211.3/2102272024-03-29T11:53:08Z2024-03-29T11:53:08ZVertical Expansion: A Solution for Future Container TerminalsZaerpour, NimaGharehgozli, AmirDe Koster, Renéhttp://hdl.handle.net/10211.3/2150842020-02-14T00:55:08Z2019-08-01T00:00:00ZVertical Expansion: A Solution for Future Container Terminals
Zaerpour, Nima; Gharehgozli, Amir; De Koster, René
Container terminals play a major role in the growth of international trade. They need to accommodate the increasing number of containers while their space is limited, particularly close to major cities. One approach, often used in practice, is horizontal expansion through expensive land reclamation projects. In contrast, vertical expansion uses the available land more efficiently by storing containers in high-bay warehouses. In this paper, we study a next generation container terminal consisting of container storage towers. A container tower is a cylindrical structure which consists of multiple levels of storage locations, lifts, and input and output (I/O) points (or depots). The lifts can rotate and can move containers horizontally and vertically to transport containers between the storage locations and the I/O points. We investigate several design questions: 1) What is the optimal configuration of a container tower? 2) How does a container tower compare to a traditional container block of the same storage capacity, in terms of throughput capacity? 3) Is a container tower financially feasible compared to an existing container block of the same storage capacity? 4) What are the impacts of varying design parameters on the container tower performance and its financial feasibility? Question 1 is answered by obtaining closed-form expressions for the tower travel time, formulating the problem as a nonlinear optimization model, and deriving closed-form expressions for the tower optimal configuration. Questions 2 and 3 are answered by using closed-form expressions in order to compare the performance of two systems. Question 4 is answered by a sensitivity analysis for the design parameters of the container tower. The results show that, compared to a traditional container block, the container tower can increase the annual throughput, while saving on the required footprint at competitive investment costs. In particular, the container tower can increase the annual throughput up to 120% compared to a container block of the same storage capacity.
2019-08-01T00:00:00ZAutomated or manual storage systems: do throughput and storage capacity matter?Zaerpour, NimaVolbeda, RosalieGharehgozli, Amirhttp://hdl.handle.net/10211.3/2150832020-02-14T00:55:01Z2019-01-01T00:00:00ZAutomated or manual storage systems: do throughput and storage capacity matter?
Zaerpour, Nima; Volbeda, Rosalie; Gharehgozli, Amir
Selecting the appropriate type of capital-intensive storage systems is an important decision for warehouse managers. However, such a decision is complex due to various available storage systems. In addition, warehouse requirements such as storage capacity and throughput influence this decision. This research provides insights that enable managers to select the suitable type of storage system which minimizes the investment and operational costs while the warehouse design requirements, in particular the storage capacity and throughput, are met. To obtain these insights, an Excel®-based decision support system is developed for a set of most common types of manual and crane-based automated storage systems in pallet and case warehouses. The decision support system uses the closed-form formulas from the warehousing literature and also Monte Carlo simulation to approximate the travel time in each storage system. The results show that the choice of automated or manual storage system and the associated costs depend on the required capacity and throughput. When the storage capacity and throughput are low, the manual pallet racks are the preferred storage system and incur the lowest costs. As the storage capacity and throughput increase, there is a need for more compact storage systems that can store more loads in a smaller footprint. Thus, for medium to high capacity levels, double-deep automated storage systems and deep-lane compact storage systems are the ones with the lowest investment and operational costs. The results for the case warehouses show that the investment and operational costs increase rapidly with an increase of the throughput. In particular, the increase is noticeable for operational costs of shelf rack system and the investment cost of miniload system where the storage capacity and throughput level are high.
2019-01-01T00:00:00ZOn the Road to Making Science of “Art”: Risk Bias in Market Scoring RulesKarimi, MajidDimitrov, Stankohttp://hdl.handle.net/10211.3/2138882019-10-16T18:44:04Z2018-05-08T00:00:00ZOn the Road to Making Science of “Art”: Risk Bias in Market Scoring Rules
Karimi, Majid; Dimitrov, Stanko
We study market scoring rule (MSR) prediction markets in the presence of risk-averse or risk-seeking agents that have unknown yet bounded risk preferences. It is well known that if agents can be prescreened, then MSRs can be corrected to elicit agents’ beliefs. However, agents cannot always be screened, and instead, an online MSR mechanism is needed. We show that agents’ submitted reports always deviate from their beliefs, unless their beliefs are identical to the current market estimate. This means, in most cases it is impossible for a MSR prediction market to elicit an individual agent’s exact belief. To analyze this issue, we introduce a measure to calculate the deviation between an agent’s reported belief and personal belief. We further derive the necessary and sufficient conditions for a MSR to yield a lower deviation relative to another MSR. We find that the deviation of a MSR prediction market is related to the liquidity provided in the MSR’s corresponding cost-function prediction market. We use the relation between deviation and liquidity to present a systematic approach to help determine the amount of liquidity required for cost-function prediction markets, an activity that up to this point has been described as “art” in the literature.
2018-05-08T00:00:00ZLocating Service Facilities with Concave Variable CostsAboolian, RobertCarrizosa, EmilioGuerrero, VanesaWang, Jiaminhttp://hdl.handle.net/10211.3/2138742019-10-16T16:04:02Z2019-02-01T00:00:00ZLocating Service Facilities with Concave Variable Costs
Aboolian, Robert; Carrizosa, Emilio; Guerrero, Vanesa; Wang, Jiamin
We consider a nonlinear version of the Uncapacitated Facility Location Problem (UFLP). The total cost in consideration consists of a fixed cost to open facilities, a travel cost in proportion to the distance between demand and the assigned facility, and an operational cost at each open facility, which is assumed to be a concave nondecreasing function of the demand served. Thus we call the problem Uncapacitated Facility Location Problem with Concave Operating Cost (UFLPCOC). Specifically, we assume that service facilities are to be located and customers seek service from the closest open facility. As a consequence, an explicit constraint is needed in the model to impose closest assignment. An exact solution approach, which is called the Search and Cut algorithm, is presented. This approach is mainly based on sequentially improving the lower and upper bounds for UFLPCOC. Lower bounds are obtained by solving a UFLP model with extra linear constraints. To find an upper bound, we present a heuristic that is based on a neighborhood search procedure starting from the solution to a mixed integer programming model. An approximation solution approach is also suggested that explores linear approximation to transform the model into a mixed integer linear programming problem. Computational results are presented. It is found that the cost structure has a significant effect on intractability of the problem and that the Search and Cut algorithm dominates the approximation solution approach in general.
2019-02-01T00:00:00Z