Research of order allocation model based on cloud and hybrid genetic algorithm under ecommerce environment

For massive order allocation problem of the third party logistics (TPL) in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm (GA), implementing cloud deployable MapReduce (MR) code to parallelize allocation process, using heuristic rule to fix illegal chromosome during encoding process and adopting mixed integer programming (MIP) as fitness function to guarantee rationality of chromosome fitness. The simulation experiment shows that in mass processing of orders, the model performance in a multi-server cluster environment is remarkable superior to that in stand-alone environment. This model can be directly applied to cloud based logistics information platform (LIP) in near future, implementing fast auto-allocation for massive concurrent orders, with great application value.     

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

The transition to electric bikes in China: history and key reasons for rapid growth

Annual electric bike (e-bike) sales in China grew from 40,000 in 1998 to 10 million in 2005. This rapid transition from human-powered bicycles, buses and gasoline-powered scooters to an all-electric vehicle/fuel technology system is special in the evolution of transportation technology and, thus far, unique to China. We examine how and why e-bikes developed so quickly in China with particular focus on the key technical, economic, and political factors involved. This case study provides important insights to policy makers in China and abroad on how timely regulatory policy can change the purchase choice of millions and create a new mode of transportation. These lessons are especially important to China as it embarks on a large-scale transition to personal vehicles, but also to other countries seeking more sustainable forms of transportation.

Design and development of a stated choice experiment for interdependent agents: accounting for interactions between buyers and sellers of urban freight services

Stated choice experiments have proven to be a powerful tool in eliciting preferences across a broad range of choice settings. This paper outlines the elements of a group-based experiment designed for interdependent urban freight stakeholders, along with the procedure to administer the questionnaire sequentially. The focus is on the design of a computer-assisted personal survey instrument and the value in disseminating the details of a new approach to design and collect stated choice data for interacting agents. The paper also discusses how to specify a reference alternative, and then how to recruit appropriate real-market or representative decision-making group members to participate in a subsequent phase of the survey, which incorporates the reference alternative and contextual information from an initial phase. The empirical strategy, set out in some detail, provides a new framework within which to understand more fully the role that specific attributes, such as variable user charges, influencing freight distribution chains might play, and who in the supply chain is affected by specific attributes in terms of willingness to pay for the gains in distribution efficiency.

Climate change and the prospects of increased navigation in the Canadian Arctic

There is wide recognition that the process of climate change may be affecting the Arctic region at a faster pace than other regions. What is uncertain is the full impact of climate change on ice cover, and in particular whether there will be a significant decrease of summer ice from the current three months to a longer period and accompanied by navigation conditions suitable and safe for commercial shipping. New international navigation routes through the Canadian and Russian Arctic sectors could significantly reduce the length of sea voyages from Asia to North America and Europe. However, on the basis of what is known to date, there are significant differences of view as to the feasibility of international commercial navigation in the Northwest Passage.     

Essentials of general average: A synoptic overview of an ancient maritime law

This article provides a synoptic overview of the concept of general average which is one of the saving acts in maritime law. Its principles were entrenched in the Roman law which acknowledged its origins being rooted in the Sea Law of Rhodes. Its evolution as customary law through the medieval maritime codes of the Mediterranean region is also traced in the article. The reader is then brought into the modern era of the international regime of general average through the advent of the York-Antwerp Rules. The basic principles of general average loss, including expenditures and sacrifices, and general average contributions are introduced through references to a number of leading cases. The current status of this ancient law and practice and debates over its future are briefly addressed in conclusion.     

Structural-acoustic optimization of stiffened panels based on a genetic algorithm

For the structural-acoustic radiation optimization problem under external loading,acoustic radiation power was considered to be an objective function in the optimization method. The finite element method(FEM) and boundary element method(BEM) were adopted in numerical calculations,and structural response and the acoustic response were assumed to be de-coupled in the analysis. A genetic algorithm was used as the strategy in optimization. In order to build the relational expression of the pressure objective function and the power objective function,the enveloping surface model was used to evaluate pressure in the acoustic domain. By taking the stiffened panel structural-acoustic optimization problem as an example,the acoustic power and field pressure after optimized was compared. Optimization results prove that this method is reasonable and effective.     

Life-style and travel demand

(Added to the original text) A fundamental solution to the issue of congestion cannot be reached without addressing the question of life-style. This paper reviews the definitions of life-style found in the literature, and identifies variables that have been commonly associated with life-style. Using US consumer expenditure data, life-styles are analyzed longitudinally (examining trends during the 1953–1983 time frame) and cross-sectionally (comparing segments of the population stratified by income, life-cycle stage, and age), and likely relationships to travel behavior are noted. The usefulness of existing empirical findings to long-range forecasting is explored by speculating on shifts of behavioral units across life-style segments, and on shifts in the behavioral patterns within each life-style segment.     

A co-integration approach to forecasting container carriers’ time charter rates

A vector autoregressive model was developed for a sample of container carrier time charter rates.Although the series of time charter rates are themselves found non-stationary, thus precluding the use of manymodeling methodologies, evidence provided by co-integration tests points to the existence of stable long-termrelationships between the series. An assessment of the forecasts derived from the model suggests that the spec-ification of these long-term relationships does not improve the accuracy of long-term forecasts. These resultsare interpreted as a corroboration of the efficient market hypothesis.     

Small area estimates of daily person-miles of travel: 2001 National Household Transportation Survey

The National Household Transportation Survey (NHTS) was designed at the national level, and for most states it does not have a large enough sample to produce reliable estimates, especially for subdomains (e.g., age groups) within a state. Using the 2001 NHTS, we produced small area estimates (SAEs) of the percentage of persons among four age groups (17 or younger, 18–39, 40–54, and 55 or older) having high daily person-miles of travel (more than 87.5 miles a day, which is the 90th percentile for daily person-miles traveled) and associated prediction intervals for all 50 states and the District of Columbia. The survey weighted hierarchical Bayes (Folsom et al., Proc of the Sect on Surv Res Methods of the Am Stat Assoc 371–375, 1999) small area estimation (SAE) methodology was used to produce state-level SAEs. This paper describes the methodology and shows that SAE can be an effective technique for producing reliable state-level estimates from large, national surveys like the NHTS. In particular, the prediction interval relative widths for SAEs were, on average, 31–48% narrower than the corresponding design-based confidence interval widths, whereas for small states the reduction was around 47–63%.