The Stochastic Container Relocation Problem

The Container Relocation Problem (CRP) is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. However, the assumption of knowing the full retrieval order of containers is particularly unrealistic in real operations. This paper studies the stochastic CRP (SCRP), which relaxes this assumption. A new multi-stage stochastic model, called the batch model, is introduced, motivated, and compared with an existing model (the online model). The two main contributions are an optimal algorithm called Pruning-Best-First-Search (PBFS) and a randomized approximate algorithm called PBFS-Approximate with a bounded average error. Both algorithms, applicable in the batch and online models, are based on a new family of lower bounds for which we show some theoretical properties. Moreover, we introduce two new heuristics outperforming the best existing heuristics. Algorithms, bounds and heuristics are tested in an extensive computational section. Finally, based on strong computational evidence, we conjecture the optimality of the “Leveling” heuristic in a special “no information” case, where at any retrieval stage, any of the remaining containers is equally likely to be retrieved next

Diosmetin Mitigates Cognitive and Memory Impairment Provoked by Chronic Unpredictable Mild Stress in Mice

Background and Aim. Numerous reports have indicated that dealing with stressors in life is a main risk factor for the occurrence and progression of cognitive and memory impairment. Available treatments such as benzodiazepine and antidepressants address only certain aspects of this stress disorder and have numerous side effects. The present study was aimed at investigating the effect of diosmetin, as a flavonoid compound with potent antioxidant and anti-inflammatory effects, on cognitive impairment and chronic stress memory. Materials and Methods. In the present experimental study, male NMRI mice were exposed to chronic unpredictable mild stress (CUMS) paradigm for 35 days. Diosmetin (at doses of 10, 20, and 40 mg/kg. i.p.) or diosmetin solvent (normal saline + DMSO, 1 ml/kg; i.p.) was administered 30 min before stress induction. After 28 days, memory and cognitive performance were assessed by shuttle box and novel object recognition tests. Finally, antioxidant capacity (FRAP) and malondialdehyde (MDA) level of serum and brain, and serum corticosterone level were evaluated. Results. Behavioral tests showed that CUMS significantly reduced the secondary latency in passive avoidance memory test and diagnosis index in novel object recognition test compared to the control group (P<0.001), whereas treatment with diosmetin (20 and 40 mg/kg) significantly improved memory performance in the two tests (P<0.001). In addition, diosmetin (40 mg/kg) could pronouncedly suppress increase in serum corticosterone levels, reduction in antioxidant capacity, and production of excess MDA caused by CUMS compared to the control group (P<0.01, P<0.001, and P<0.001, respectively). Conclusion. Chronic stress can impair memory and cognition and treatment with diosmetin can partly improve this disorder in male mice by increasing the antioxidant capacity of brain tissue and serum and improving serum corticosterone levels

Influence Of Brand Personality On Brand Equity For Internet Service Provider (ISP\'S) In Malaysia

The Internet service providers (ISPs) play a vital role in the ICT industries in any country and specifically, provide a crucial role in the economical prosperity of Malaysia. Strong brand personality definitely is a critical factor to enhance customer based brand equity of ISPs that help them not only to have a better influence on the customers inside Malaysia but to prepare Malaysian ISPs to compete with the international markets as well

Optimization of yard operations in maritime container terminals

Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2015.Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (pages 107-109).With the continuous growth in international container shipping, many container terminals in maritime ports face congestion, particularly during peak hours of service, and when there is limited space in the storage area. Thus, there has been increasing interest in improving operations efficiency in container terminals. An efficient terminal, in general, is one that discharges containers from the ships in a timely manner and delivers containers to customers with a reasonable wait time. Moreover, a key performance measure in the storage area is the number of moves performed by yard cranes. Due to limited space in the storage area, containers are stacked on top of each other, forming a column of containers that can be accessed by yard cranes only from the top. Therefore, in order to retrieve a container that is covered by other containers, the blocking containers must be relocated to other slots. Because such relocation moves are costly for the port operators and result in service delays, one of the main challenges in the storage area is to plan the moves such that the number of relocations is minimized. This problem is referred to as the Container Relocation Problem (CRP). The CRP in its most simplified setting is concerned with finding a sequence of moves that retrieves all containers in a pre-defined order with a minimum number of relocations, assuming that no new containers are stacked during the retrieval process. Also, it is often assumed that the non-blocking containers cannot be relocated (i.e., repositioning moves are not allowed), an assumption that can result in a sub-optimal solution. Other variants of the container relocation problem include the dynamic CRP and the CRP with incomplete information. The former involves minimizing the number of relocations when containers are continuously stacked in and retrieved from the storage area, and the latter refers to the case that the departure times of containers are not fully known in advance. For example, a probabilistic distribution of container departure orders, or approximate departure times (in the form of time windows) might be known. Another important efficiency metric, in addition to the number of relocations, is customer wait times during the retrieval process. In particular, when repositioning moves are allowed in the system, there is a trade-off between the total number of relocations (including repositionings) and wait times, because such repositioning moves make the retrieval process faster for trucks arriving in the future. Also, it might be desired to prioritize some customers so that those prioritized experience shorter wait times. For example, in terminals with appointment systems, shorter waiting time guarantees can be given to customers who book in advance a time slot for picking up their containers. In this thesis, we propose optimization models that capture service-based and cost-based objectives and study different service policies. In the first part of this thesis, we study the CRP with complete information using an optimization model and heuristic approach. In particular, we formulate CRP (with no restrictive assumptions on repositioning moves) as an Integer Program that minimizes the weighted sum of the number of relocations and the total wait time of customers. Our integer program provides the optimal sequence of moves for retrieving containers subject to various service policies. For example, it can be used by port operators to minimize customer wait times, or to give different waiting time guarantees to different customers to reflect relative priorities. Moreover, by assigning different weight factors to the two objectives, one can use our model to plan repositioning moves. We also extend our model to the dynamic CRP and illustrate how the flexibility in the stacking process can be exploited to optimize jointly the sequence of moves and the stacking position of containers. Additionally, we propose a class of flexible retrieval policies. We demonstrate that flexible policies can result in fewer relocations and shorter wait times, thereby benefiting both the port operators and customers. In the second part of this thesis, we study the CRP with incomplete information in a 2-stage setting where the departure times of a subset of containers are initially known and the departure times of other containers are revealed at once at a later time. The contributions are twofold. First, we propose an approximate stochastic optimization algorithm, called ASA*, which is a branch-and-bound framework combined with a sampling technique, and to the best of our knowledge is the first optimization algorithm proposed for this problem. We provide theoretical bounds on the approximation errors and present numerical results showing the computational tractability and efficiency of our algorithm. Second, we use the ASA* algorithm and a myopic heuristic to study the value of information, that is, the effect of the number of containers initially known on the number of relocations. In the last part of this thesis, we introduce a simulator that is capable of integrated simulation of port operations, including the retrieval process, the stacking process, and other aspects such as allocating cranes to containers and allocating trucks to cranes. Our simulator captures the practical details of operations that cannot be modelled in an optimization framework and is capable of simulating long periods (e.g. a week) of realistic-scale operations.by Setareh Borjian Boroujeni.S.M. in TransportationS.M

A Novel Replication Strategy for Efficient XML Data Broadcast in Wireless Mobile Networks

Recently, the use of XML for data broadcasting in mobile wireless networks has gained many attentions. In these networks, a stream of XML data is broadcasted via a wireless channel, and mobile clients access the broadcast stream using energy-restricted portable devices. Several indexing methods have been proposed to selectively access XML data over a broadcast stream. Although existing indexing methods improve the performance of XML query processing in terms of access time and tuning time but they do not use a replication strategy to replicate the indexes in the broadcast XML stream. In this paper, we propose a novel replication strategy for XML data broadcast called Triangle- based Replication (TR) strategy which replicates the partial and relevant parts of indexes into suitable positions in the broadcast XML stream. Experimental results show that our proposed XML replication strategy has better performance compared to existing XML replication strategies

Molecular and Parasitological Study of Cryptosporidium Isolates From Cattle in Ilam, West of Iran

Background: Toxoplasmosis is a worldwide spread disease. The present study examined the prevalence of Toxoplasma gondii infection among animals of ediblemeat (cattle and sheep) in Chaharmahal va Bakhtiari Province (Southwest of Iran) in 2012. Furthermore, we attempted for the first time to identify this parasite from the meat products in the province. Methods: The tongue, brain, femur muscle and liver of 50 sheep and 70 cattle as well as 50 samples of meat products were selected and collected to perform molecular survey using Nested-PCR method. Results: Of the studied sheep, 38% were infected. The infection rate in the age groups under 1 year, 1-2 years, and more than 2 years was 25%, 35.29% and 52.94%, respectively. The infection rate in femur muscle, brain, liver and tongue was 28%, 32%, 30% and 16%, respectively. Of the studied cattle, 8.57% were infected. The infection rate in the age groups 1-2 years, 2-4 years, and more than 4 years was 3.7%, 9.09% and 14.28%, respectively. Sheep was infected 6 times more than cattle (OR = 6.53 CI = 2.374-18.005).The infection rate among samples of meat products was 12% (6 samples out of 50 samples). Conclusion: Due to the high rate of this parasitic infection among the slaughtered animals as well as meat products in this region, the use of infected material can be one of the main risk factors of transmission of the parasite to humans

Detection and identification of Leishmania isolates from patients with Cutaneous Leishmaniasis (CL) in Isfahan (central region of Iran) by PCR method

Leishmaniasis is caused by parasitic protozoa of the genus Leishmania. Cutaneous leishmaniasis (CL) is a complex disease with wide spectrum of clinical manifestations. In order to identify leishmania species causing CL in Isfahan by a definite molecular technique (PCR method), this study was undertaken over 2010- 2011. 124 Patients with suspicious lesion of Leishmaniasis and positive direct smear from lesion were selected. Samples were cultured in NNN and RPMI 1640 media Negative and positive control and clinical samples was applied for PCR in the same condition. In the next step, standard PCR was carried out using classic protocol. From 124 patients, 111 (89.51%) cases were infected as L. major and 12 (9.67%) cases were infected by L. tropica, However only in one patient simultaneous infectious with both L. major and L. tropica was identified by PCR techniques which could not be possible in microscopy. L.major was the most prevalent species in the studied patients (p-value<0.001)

An average-case asymptotic analysis of the Container Relocation Problem

The Container Relocation Problem (CRP) involves finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers in a given order. In this paper, we focus on average case analysis of the CRP when the number of columns grows asymptotically. We show that the expected minimum number of relocations converges to a simple and intuitive lower-bound for which we give an analytical formula. Keywords: CRP; Asymptotic analysis; Expected lower boun

The Stochastic Container Relocation Problem

© 2018 INFORMS. The container relocation problem (CRP) is concerned with finding a sequence of moves of containers that minimizes the number of relocations needed to retrieve all containers, while respecting a given order of retrieval. However, the assumption of knowing the full retrieval order of containers is particularly unrealistic in real operations. This paper studies the stochastic CRP, which relaxes this assumption. A new multistage stochastic model, called the batch model, is introduced, motivated, and compared with an existing model (the online model). The two main contributions are an optimal algorithm called Pruning-Best-First-Search (PBFS) and a randomized approximate algorithm called PBFS-Approximate with a bounded average error. Both algorithms, applicable in the batch and online models, are based on a new family of lower bounds for which we show some theoretical properties. Moreover, we introduce two new heuristics outperforming the best existing heuristics. Algorithms, bounds, and heuristics are tested in an extensive computational section. Finally, based on strong computational evidence, we conjecture the optimality of the "leveling" heuristic in a special "no information" case, where, at any retrieval stage, any of the remaining containers is equally likely to be retrieved next