A supply chain network design considering transportation cost discounts

This study addresses an integrated facility location and inventory allocation problem considering transportation cost discounts. Specifically, this article considers two types of transportation discounts simultaneously: quantity discounts for inbound transportation cost and distance discounts for outbound transportation cost. This study uses an approximation procedure to simplify DC distance calculation details, and develops an algorithm to solve the aforementioned supply chain management (SCM) problems using nonlinear optimization techniques. Numerical studies illustrate the solution procedures and the effects of the model parameters on the SCM decisions and total costs. Results of this study serve as a reference for business managers and administrators.     

Exploring impact factors of shippers’ risk prevention activities: A European survey in transportation

This paper reports results of a survey examining the impact factors for shippers to implement risk prevention activities. A regression analysis illustrates the relations between risk and quality related impact factors and the shippers’ ability to implement risk prevention activities. The study identifies the corporate risk culture and product vulnerability as main impact factors for the implementation of prevention activities in transportation. This paper will be beneficial for transportation managers considering the implementation of risk prevention activities in the transportation field, and will support further empirical research in the transportation management and supply chain risk management research area.     

A hybrid decomposition algorithm for designing a multi-modal transportation network under biomass supply uncertainty

This study presents a two-stage stochastic programming model for the design and management of a biomass co-firing supply chain network under feedstock supply uncertainty. To represent a more realistic case, we generate scenarios from prediction errors of the historical and forecasted biomass supply availabilities. We solve the model using a hybrid decomposition algorithm that combines Sample average approximation with an enhanced Progressive hedging algorithm. The proposed algorithm is validated via a real-world case study using data from Mississippi and Alabama. Computational results indicate that the proposed algorithm is capable of producing high quality solutions in a reasonable amount of time.     

A heuristic algorithm for yard truck scheduling and storage allocation problems

The yard truck scheduling and the storage allocation are two important decision problems affecting the efficiency of container terminal operations. This paper proposes a novel approach that integrates these two problems into a whole. The objective is to minimize the weighted sum of total delay of requests and the total travel time of yard trucks. Due to the intractability of the proposed problem, a hybrid insertion algorithm is designed for effective problem solutions. Computational experiments are conducted to examine the key factors of the problem and the performance of the proposed heuristic algorithm.     

The influence of green practices on supply chain performance: A case study approach

The main objective of this exploratory paper is to investigate the relationships between green practices of supply chain management and supply chain performance. This relationship is investigated in the context of the automotive industry. Five research propositions are suggested and tested with empirical data derived from five case studies taken from the Portuguese automotive supply chain. The data analysis identifies the most important green practices considered by managers, as well as the performance measures that are most appropriate and most widely used as means to evaluate the influence of green practices on supply chain performance. A conceptual model was derived from the data analysis and it can be used to assess the influence of green practices on supply chain performance. This model provides evidence as to which green practices have positive effects on quality, customer satisfaction and efficiency. It also identifies the practices which have negative effects on supply chain performance.     

Greening transportation fleets: Insights from a two-stage game theoretic model

The greening of organizational transportation fleets, especially trucks and automobiles, has gained increasing attention by companies in a variety of industrial sectors. The reasons for this concern and attention are due to regulatory and competitive pressures, but also increasing costs of fossil-fuels. Surprisingly the amount of research and modeling for fleet management overall has been rather limited, with the focus on managing green vehicle investments virtually non-existent. In this study we develop a two-stage game theoretic model that helps evaluate, from both policy and organizational perspectives, the implications of greening of transportation fleets. Various parameters are evaluated including factors such as innovations in green vehicle technology, levels of service differences, cost of fuel, adjusting tax policy, regulatory compliance requirements, and adaptation costs. This evaluation provides practical insights into actions that could be considered by regulators and organizations to encourage environmental investments.     

Performance measurement of a transportation network with a downtown space reservation system: A network-DEA approach

We propose an evaluation approach for a novel travel demand management strategy known as the downtown space reservation system (DSRS). This approach takes into account three perspectives, i.e., transportation service provider’s, the user’s, and the community’s and is based on network-Data Envelopment Analysis (DEA) where the perspectives are inter-related through intermediate inputs/outputs. Two types of network-DEA models (radial and slacks-based models) are considered. An example is provided using data propagated from a microscopic traffic simulation model of the DSRS. The results show that individual node performance can drive network DEA performance and that this information can inform future designs of the DSRS.     

Reprint of “Green supply chain decisions – Case-based performance analysis from the food industry”

Environmental impacts, such as GHC emissions, have been introduced to supply chain management as an additional parameter to traditional cost, lead-time and on-time delivery. Supply chain management represents a significant source of decisions affecting the eco-efficiency of many products. This paper analyses cases from the food industry, mainly order-picking, transportation, warehousing, and distribution aspects from the greening point of view. Three case examples of decisions in supply chain design in the food industry are considered. The results show dependencies between performance measures. Finally, a framework of decisions and their impact on performance is presented.     

A method to assess the eco-efficiency of a public bus transportation service

Brazilian Public Bus Transportation Service transports over 34.4 million passengers daily using approximately 107,000 urban buses. This service costs millions of dollars annually to the municipality and emits several pollutants to the atmosphere. Therefore, this paper proposes a method to assess the eco-efficiency of a Public Bus Transportation Service. The proposed method was tested in a medium-sized urban region in Brazil. Different scenarios representing changes in the vehicles engines and fuels were tested and analyzed. Six eco-efficiency indicators regarding emissions and fuel consumption were proposed to assess which mix of engines and fuels would bring the greatest eco-efficiency. The results were compared to targets based on Brazilian regulation and showed that the renewal of the fleet is necessary to meet the environmental targets, while also achieving fuel costs reduction.     

城际铁路列车停站方案的遗传算法求解

我国城市群快速发展,城市间人员交流密切频繁,城际铁路成为城际间旅客的重要出行方式。合理的城际铁路列车停站方案可以提高城际铁路的竞争力,提升城际铁路的分担率。分析停站方案相关的运营收益和旅客出行成本,以铁路运营收益最大和旅客出行成本最小为目标函数,以车站服务频率、设备能力、列车停站次数等作为约束条件,建立城际铁路列车停站方案的多目标混合0-1规划模型,运用理想点法和遗传算法求解。算例结果表明,该模型和算法可以优化得到铁路运营收益和旅客出行成本均较优的停站方案。