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The purpose of this paper was to determine the effect of route optimization on travel distance, travel time and fuel consumption of municipal solid waste (MSW) collection trucks.

The study modeled the existing waste collection routes in three local authorities in Ghana and proposed optimal routes using Esri’s ArcGIS Network Analyst Extension. The system generated optimal distances and times were validated by subjecting collection trucks to the optimal routes. Paired sample t-test was used to analyze the differences in means of the existing and optimal outcomes. The collected data were subjected to correlation and uncertainty analyses.

Results from the study indicated that weekly travel distance reduced by 81.27 km, translating into saving of 4.79 percent when trucks used the optimal routes. Travel time and fuel consumption reduced by 853.59 min and 145.86 L, making savings of 14.21 and 10.81 percent, respectively. Significant differences occurred between the means of the existing and optimal routes for travel time and fuel consumption, for each of the three local authorities.

The study was conducted in Ghana using data collected from three local authorities.

Significant reduction of MSW collection cost can be achieved by waste management practitioners through route optimization.

The effect of route optimization on travel distance, travel time and fuel consumption has been established. Statistical analyses of the existing and optimal outcomes of the three local authorities have been provided. The findings from this study support the hypothesis that optimal routes reduce operating cost through savings in travel distance, travel time and fuel consumption.

Logistics companies are compelled to improve their efficiency and the environmental performance by introducing the green concept in their operations. The main purpose of the paper is to have continuous monitoring and tracking of logistics operations to enhance the green performance.

This research uses a case study approach. It illustrates a monitoring system to digitize the logistics activities by sending real-time GPS data to the server and capture the surrounding pictures with the help of the internet of things (IoTs) based camera. Data generated through digitization is mathematically analyzed for ensuring a green logistic system. The alerts due to the halts, help in keeping a check on fuel consumption, carbon emissions and security of logistics. Performance indicators such as carbon emissions and the value of travel time saving (VTTS) are selected for the study.

The findings of the study show that the actual travel time and distances are higher than the estimated travel time and distances. It also reveals that actual travel routes with diversions involve a considerably higher amount of carbon emissions during all sample travels. The results indicate a considerable saving in terms of carbon emissions, time and cost savings by effective practices of Green Logistics in Monitoring system (MSGL). These findings can help the top management of logistics companies in formulating effective strategies for technology applications in logistic operations to ensure green performance.

The study has been carried out under certain set of conditions, which may vary depending upon the organizations. Also certain more environmental dimensions for performance monitoring can be used as a future scope of study. Further studies also need to be carried out to widen the scope of the MSGL model at a global level rather than only at local level.

Any organization which deploys transportation as part of their activity can use this MSGL model and then do the mathematical analysis to reduce the CO₂ emissions, reduce the time and extra cost. The value of this study lies in the fact that government is trying different methods and models to reduce pollution. This MSGL should be made compulsory by the government as a part of their policies for environment of the country.

This paper aims to examine the factors affecting travelers’ decision to select more than one destination in their trips. Drawn from the rational choice theory, this study posits that the selection of multi-destination tours, as a rational choice, is determined by the travelers’ perception of costs and benefits associated with that choice.

The conceptual model was developed from both an exploratory research with in-depth interview and the literature. A logistic regression model linking four explanatory variables representing perceived benefits and costs of multi-destination option with travelers’ choice of multi-destination trips. The conceptual model is controlled for diversity of travel purposes; tour group size; type of travel arrangement and travelers’ demographic characteristics while the research context of multi-destination travel within Phu Yen – Dak Lak – Gia Lai – Binh Dinh helps control for the characteristics of the destination set (spatial proximity and traffic convenience). The conceptual model was tested based on data collected from 1,361 Vietnamese travelers who have ever visited at least one of the four provinces.

This study finds that perceived benefits in terms of diversifying tourism experiences and perceived costs of traveling in multiple places compared to taking single trips represent the most significant drivers for tourists’ selection of multi-destination tours. In addition, the diversity of travel purposes and tour group size have a positive and significant impact on the demand for traveling more than one destination in a trip. Moreover, the richer, older and married travelers have a significantly higher tendency to select multi-destination packages.

The research findings provide important strategic implications for promoting multi-destination trips, thereby, maximizing economic benefits from tourism.

While multi-destination travel patterns have been examined empirically in individual studies sporadically without a common theoretical background, this research makes some progress on this front by using the rational choice theory to connect the relative contributions of those factors to the travelers’ choice of multi-destination trips. Specifically, this study provides a new perspective in explaining the selection of multi-destination trips – from tourists’ perceptions about costs and benefits associated with that choice.

Ramp meters in the Twin Cities were turned off for 8 weeks in the Fall of 2000. This paper analyzes traffic data collected in this experiment on travel time variability with and without ramp metering for several representative freeways during the afternoon peak period. Travel time variability is generally reduced with metering. However, it is found that ramp meters are particularly helpful for long trips relative to short trips. The annual benefits from reducing travel time variability with meters are estimated to be $33.1 million, compared to the annual ramp metering costs of $2.6 million in the Twin Cities metro area. Thus, the impact on travel time variability should be captured in future ramp metering benefit/cost analysis.

The expected benefits of newly developed transportation infrastructures are the saving of travel time and further promoted transport economics. There is a need for a methodology of travel time estimation with acceptable robustness and practicability. Macroscopic fundamental diagram (MFD) represents the overall traffic performance at a network level by linking average flow, speed and density. MFD can be used to estimate network state and to describe various traffic management strategies. This study aims to describe the effect of new infrastructure development on the network performance using the MFD framework.

The scenarios of Islamabad Road network before and after the infrastructure construction were simulated, in which the floating car data set (FCD) for multiple modes was extracted. MFD has been formed for the whole region and partitioned region, which was divided on the basis of infrastructural changes. Moreover, this study has been extended to calculate travel time for multiple modes using the MFD results and the Bureau of Public Roads (BPR) function at a neighborhood level.

MFD results for the whole network showed that the speed of traffic improves after the construction of new infrastructure. The travel time estimates using MFD results were dependent on the speed estimates, whereas the estimates obtained using the BPR function were found to be dependent on the traffic volume variation during different intervals of the day. By using the FCD for multiple modes, travel time estimates for multiple modes were obtained. The BPR function method was found valid for estimating travel time of traffic stream only.

This paper innovatively investigates the change in network performance for pre-construction and post-construction scenarios using the MFD framework. In practice, the approach presented can be used by transportation agencies to evaluate the effect of different traffic management strategies and infrastructural changes.