Uncertain transport environment

With a shorter planning horizon and an overall objective of minimizing enterprises costs, transportation has become a critical component in the distribution process (Tyan et al., 2003). Globalization force companies to redesign or manage their supply chain efficiently whereas transportation and logistics are drivers in world trade. Global transportation uncertainties are dramatically rising in light of volatile demand and international logistics. In literature of supply chain management, there are lots of studies that have conducted the role of transportation and logistics operations within a supply chain. Vidal and Goetschalckx (2000) model the effect of uncertainties on global logistics systems at international level, including exchange rate fluctuation, stochastic demand, political instability, variable transportation lead time and market prices with the objective of minimizing supply chain costs that include procurement, production, transportation and fixed plant and inventory costs. Das and Sengupta (2009) studied the global and multinational companies are subject to government regulation in addition to other international uncertainties due to operation in diverse geographic locations. The paper presents an integrated model for simultaneous strategic and operational planning in a global supply chain affected by government regulations. At operational level, the proposed model assesses customer demand and transportation time uncertainties to aid decisions regarding production, the transportation and distribution of

regulations, variable transportation time and cost, and capacity are taking into consideration as transport uncertainties with particular emphasis on transport modes and the transportation channels to use. This view is strengthened by Punakivi and Hinkka (2006), taking the selection criteria of transportation modes from the four Finnish industrial points as the main research problem. Based on the results, high value, short life cycles and worldwide market are typical to use rapid modes of transport.

Cullinane and Toy (2000) adapt the Stated Preference (SP) techniques to identify the major influential attributes in freight route/ mode choice, including transit time reliability, speed, cost, and loss/damage.

Jong et al. (2004) contain a review of the literature on freight transport models for forecasting, policy simulation and project evaluation at the national and international levels. Haughton (2007) models situation in which random day-to-day demands complicate decisions made by managers of vehicle routing/dispatch operations. The paper proposes a rule by trying to maximize the likelihood that each customer will continue to be served by the driver who is most familiar with that customer.

Li et al. (2008) present a coordinated scheduling problem of parallel machine assembly manufacturing and multi-destination transportation in consumer electronics supply chain by dividing into two sub-problem, to respond the shorten time from order receipt to delivery and improve on-time delivery accuracy. The proposed model determines the

the problem.

Motivated by observing the chemical industries, Kiesmüller et al.

(2005) presented a dual supply model taking into account that the replenishment cycle involves not only the physical distribution of goods, but also the manufacturing of products. This study also investigated a class of order-up-to policies and showed how to compute the optimal policy parameters. The results showed that especially in cases where the manufacturing lead time is long and the difference in cost between fast and slow modes is big and the lead time difference is large, the added value of including the manufacturing lead time for the model is substantial. In industries such as the chemical industry using the models would imply a dramatic shift from road transport to rail or barge transport.

Additionally, Eskigun et al. (2005) design an outbound supply chain network considering lead times, location and capacitated of vehicle distribution facilities, and the choice of transportation mode in the automotive industry. A Lagrangian heuristic is conducted to solve the integer linear programming (ILP) problem. Results of the scenario analyses indicate that as the lead-time gains importance, the use of trucks increases significantly to deliver the vehicle directly from plants to demand areas in shorter lead-time. In addition, this study also determines the vehicles delivery directly to demand areas or through a distribution center, based on domestic intermodal transportation and route selection.

transportation modes and demanded delivery times; and (3) transportation economies of scale. The study formulates a multi-objective multi-modal multi-commodity flow problem (MMMFP) with time windows and concave costs and develops a heuristic algorithm base on relaxation and decomposition techniques.

As mentioned above, intermodal freight transport has developed into a significant part of transport industry in its own. It reflects the combination of at least two modes of transport in a single transport chain.

Several authors have explored about the intermodal transportation related issues. Bookbinder and Fox (1998) obtain the optimal routings for intermodal containerized transport from Canada to Mexico. Each link employs available intermodal services with given its transit time and transportation cost. A shortest path algorithm enables calculation of the route requiring least time and the route of minimum cost. The results show the non-dominated time/cost tradeoff relationship. Macharis and Bontekoning (2004) review related operational research literatures and point out mostly works are focus on single modal transportation problem.

They also argue the intermodal freight transportation is emerging as a new transportation research application field.

Woxenius (2007) described six principles for design of transport systems, including direct link, corridor, hub-and-spoke, connected hubs, static routes, and dynamic routes. The theory is then applied to intermodal freight transport by comparing the terminology from the perspectives of

shipments sizes, high frequencies, and the fragmentation of flows. This study models the collaborative, intermodal hub networks with shifting consolidated flows to modes to synchronization between expensive but fast and flexible means of transport and inexpensive, but slow and inflexible means through collaboration. The resulting methodology is explained through presenting the results of the design and implementation of collaborative hub network for the distribution of fast moving consumer goods using a combination of trucking and inland barges. Table 2.4 summarizes main issues and results in literature on uncertain transport environment.

Summary:

Past literatures have demonstrated the importance of logistics and transportation on the efficiency of a supply chain. Moreover, global transportation environment uncertainties are dramatically rising in light of volatile demand and international logistics with time shifting. Regarding to the uncertain factors, such as transport modes choices/intermodal, paths/ routes selection, variable transit cost and time, demand fluctuation, facility capacity, exchange rate between each country, and government regulations, have been investigated as emerging research topics and applications. However, these transport uncertainties are only explored partially or as conceptual issues in recent research, not considered as the main problem on the distribution model.

Table 2.4 Main issues and results in literature on uncertain transport environment

Authors Main issues Important results Goetschalckx

(2000)

Modeling the effect of uncertainties on global logistics systems

The proposed model demonstrates the effect of uncertainties is significant that may differ with small changes in some parameters.

Das and

The results show that the decision makers must aim at optimal redeployment of available capacity if

government regulations lead to changes in the cost of input resources. include transit time, cost, reliability, and types of dispatched products.

The results of the difference in cost and transportation time between fast and slow modes, available vehicle capacities, and demand will affect the total benefit and the route/mode choices. based on domestic and international

The models reflect multiple objectives, delivery lead times, transportation modes, locations, capacity, and

Authors Main issues Important results

transportation is emerging as a new transportation research application field in recent years. with shifting flows and modes to

synchronization

between expensive but fast and flexible of transport and

inexpensive, but slow and inflexible means through collaboration.

The resulting methodology is explained through presenting the results of the design and implementation of

collaborative hub network for the distribution of fast

moving consumer goods using a combination of trucking and inland barges.

Source: this study