Search results

In this paper, the authors introduced a real world new problem, the multi-trip vehicle routing problem with time windows and the possible use of a less-than-truckload carrier to satisfy customer demands. The purpose of this paper is to develop a heuristic algorithm to route the private trucks with time windows and to make a selection between truckload and less-than-truckload carriers by minimizing a total cost function.

Both mathematical model and heuristic algorithm are developed for routing the private trucks with time windows and for selecting of less-than-truckload carriers by minimizing the total cost function.

In all, 40 test problems were examined with the heuristics. Computational results show that the algorithm obtains the optimal or near-optimal solutions efficiently in terms of time and accuracy.

The research described in this paper differs from the previous one on fleet planning or vehicle routing, in that it modifies the Clarke and Wright method by shifting the performance measure from a distance to cost and also incorporates the fixed cost of different types of trucks into the model. In addition, the authors simultaneously consider the multiple trip vehicle routing problems with time windows and the selection of less-than-truckload carriers that is an integrated scenario of real-world application. To the best of the authors’ knowledge, this scenario has not been considered in the literature.

This purpose of this paper is to present a methodology for optimally planning long‐haul road transport activities through proper aggregation of customer orders in separate full‐truckload or less‐than‐truckload shipments in order to minimize total transportation costs.

The model is applied to a specific Italian multi‐plant firm operating in the plastic film for packaging sector. The method, given the order quantities to be shipped and the location of customers, aggregates shipments in subgroups of compatible orders resorting to a heuristic procedure and successively consolidates them in optimized full truck load and less than truck load shipments resorting to a Genetic Algorithm in order to minimize total shipping costs respecting delivery due dates and proper geographical and truck capacity constraints.

The paper demonstrates that evolutionary computation techniques may be effective in tactical planning of transportation activities. The model shows that substantial savings on overall transportation cost may be achieved adopting the proposed methodology in a real life scenario.

The main limitation of this optimisation methodology is that an heuristic procedure is utilized instead of an enumerative approach in order to at first aggregate shipments in compatible sets before the optimisation algorithm carries out the assignments of customer orders to separate truckloads. Even if this implies that the solution could be sub‐optimal, it has demonstrated a very satisfactory performance and enables the problem to become manageable in real life settings.

The proposed methodology enables to rapidly choose if a customer order should be shipped via a FTL or a LTL transport and performs the aggregation of different orders in separate shipments in order to minimize total transportation costs. As a consequence, the task of logistics managers is greatly simplified and consistently better performances respect manual planning can be obtained.

The described methodology is original in both the kind of approach adopted to solve the problem of optimising orders shipping in long‐haul direct shipping distribution logistics, and in the solution technique adopted which integrates heuristic algorithm and an original formulation of a GA optimisation problem. Moreover, the methodology solves both the truckload assignment problem and the choice of LTL vs FTL shipment thus representing an useful tool for logistics managers.

The challenge of truckload routing is increased in complexity by the introduction of stochastic demand. Typically, this demand is generalized to follow a Poisson distribution. In this chapter, we cluster the demand data using data mining techniques to establish the more acceptable distribution to predict demand. We then examine this stochastic truckload demand using an econometric discrete choice model known as a count data model. Using actual truckload demand data and data from the bureau of transportation statistics, we perform count data regressions. Two outcomes are produced from every regression run, the predicted demand between every origin and destination, and the likelihood that that demand will occur. The two allow us to generate an expected value forecast of truckload demand as input to a truckload routing formulation. The negative binomial distribution produces an improved forecast over the Poisson distribution.

Consolidation of inbound freight is one way in which procurement costs might be reduced. Can it compete with direct shipments from vendors?

Reports on the status of electronic data interchange (EDI) usage by motor carrier firms in 1994. The same methodology was employed as in a similar study conducted in 1991, thereby permitting a comparison of practice between these two time periods. The results indicate that a number of changes have occurred between 1991 and 1994. For example, as carriers have become more experienced with EDI, their EDI services offerings have become a larger percentage of their freight revenues. New problems have arisen (e.g. organizational barriers) as carriers integrate EDI more completely. On the other hand, the results also indicate where change has not occurred. Technical standards remain a “non issue” for carriers, yet finding relevant software remains an issue. Examines these and other findings and discusses their implications.

Presents a fourth generation language computer simulation model which was developed for a major US manufacturing company. Suggests that marketing and logistics managers can benefit from business planning models that simulate the financial impact of their decisions. To be effective, models must have the ability to evaluate the impact of changes in the marketing mix on product and customer profitability. Sound business decisions follow from knowledge of the behaviour of expenses, especially those associated with logistics and for assets employed.

The paper aims to analyse the reasons behind the leadership shown by a case study retailer through the introduction of factory gate pricing (FGP) within the grocery sector. Further, there is an evaluation of the transport management techniques used to support FGP and the operational benefits gained.

The research is based around a single case study of a UK grocery retailer, which has adopted FGP. A range of data sources has been collected during a project with the retailer. Techniques used include process mapping, interviews, workshops and company presentations.

Strategically, the introduction of FGP has provided economies for the retailer strengthening its position in the market. Four main transport management techniques have been deployed to achieve this, generating reductions in transport and inventory costs while improving customer service levels. There are also some issues that need addressing, in relation to the need for a single point of control, who manages this point and the technological capabilities of transport providers.

Only a single case study is presented, and the research was carried out during the early phase of implementation.

FGP requires a certain degree of scale to be effective, and should complement current processes within a business. There is a need to manage relationship issues with suppliers and transport providers.

The paper presents a detailed case study of FGP within the grocery sector, which is more complex than previous application of the concept. The strategic rationale for pioneering FGP is considered, along with its tactical deployment and operational benefits. Concerns are also highlighted, to provide a balanced evaluation.

Recent supply chain disruptions have highlighted the global shortage of truck drivers. Because it is a quintessential “masculine” profession, the proportion of women truck drivers is small, although efforts are underway to recruit and retain women. This research offers a comprehensive and theoretically-driven empirical analysis of women in the US trucking industry.

The research utilizes a detailed longitudinal database of 20 million driver inspections from 2010 to 2019. It is paired with US Social Security Administration data to infer the gender of the driver for each inspection. Descriptive evidence is provided, and a logit model is used to test the hypotheses.

The research finds that female truck drivers make up 3.2% of the inspection sample, but their representation has grown by 23.1% over the last decade. Women are vastly overrepresented in the jobs that are the easiest to get and underrepresented in jobs that offer better pay, more regular hours and more time at home. However, the proportion of women in more desirable truck driving jobs has grown from 2010 to 2019, offering positive news for the industry.

The research offers a more credible and realistic statistic for the proportion of women in the industry, contradicting previous industry figures. The research also highlights policy implications for industry stakeholders.

The truck driving industry is vital for a nation's economic sustainability. Truck driving jobs offer better wages and more opportunity than many non-professional female-dominant jobs. The research emphasizes the path to move into jobs that are better suited for women with domestic or family responsibilities.

The authors document hitherto unknown facts about women in the US trucking industry. Using theoretically driven research in organizational science, this study highlights the interplay of supply-side and demand-side factors that help to explain a nuanced perspective of the workforce composition and discusses potential policies to increase the number of female drivers.

The purpose of this paper is to compare small and large motor carriers to determine whether small motor carriers serve a smaller, more concentrated customer base, have owners that are more involved in the customer relationship management process, and earn higher returns usually associated with niche market players.

Responses from a US sample of 153 motor carrier managers are subjected to ANOVA comparing small, medium, and large motor carriers. Scale development procedures were employed and a construct measuring owner involvement in the customer relationship management process was developed.

Small motor carriers have a more concentrated customer base, their owners are more involved in managing customer relationships, and they are paid higher rates per mile compared with large motor carriers.

This research was limited by its focus on the motor carrier industry and did not explicitly test a link between customer base concentration and owner involvement as they might engender higher rates.

This work illustrated motor carrier practices that may be of use to managers in formulating strategy. Managers may also consult the owner involvement construct items for guidance in their customer relationship management role.

This is one of the few works investigating small motor carriers. It also is one of the first works incorporating entrepreneurship into logistics research.

The purpose of this paper is to examine the past 50 years of driver research from a historical context linked to the political and economic developments of the US motor carrier industry.

A comprehensive literature review was conducted and studies were targeted that exemplified eras of historic change pertaining to trucking published within the top-tier logistics journals.

Distinctive categorizations of driver research emerged: organizing era from 1930 to 1949, era of the collective mind from 1950 to 1979, era of the individual from 1980 to 2009 and the era of the driver as extension of the firm from 2010 to present. Research streams are highly influenced by current industry developments, economic conditions and the political landscape.

The chronological framework of research established specific time-based eras. An alternative framework or other emerging eras may be conceived as scholars consider factors in addition to those explored within this research.

Managers within developing countries may leverage the research within a specific era to help resolve driver problems that have already been researched in the USA. Scholars are encouraged to further study truck drivers as critical extensions of the firm in light of the advances in autonomous vehicles, drones and other technology impacting the motor carrier industry.

For nearly a half century, the turnover of truck drivers has been a major issue. This research provides driver managers with the knowledge to better understand and to more adequately provide for the needs and welfare of truck drivers.

This research is the first to fully connect the research and developments pertaining to the motor carrier industry, the occupation of truck driving and the historical developments of US policy and the economy.