The capacitated plant location problem with customers and suppliers matching

This paper introduces a new problem called the capacitated plant location problem with customer and supplier matching (CLCSM). The product distribution from plants to customers and the material supply from suppliers to plants are considered together. We merge a distribution trip and a supply trip into one triangular trip for saving allocation cost. Vehicles from plants visit a customer and a supplier for each trip. We provide a heuristic solution procedure based on Lagrangian relaxation. Computational results indicate that the proposed heuristic solution procedure is shown to be efficient yielding optimal or near-optimal solutions for randomly generated instances.     

A three-level supply chain network design model with risk-pooling and lead times

This paper considers a single-sourcing network design problem for a three-level supply chain consisting of suppliers, distribution centers (DC’s) and retailers, where risk-pooling strategy and DC-to-supplier dependent lead times are considered. The objective is to determine the number and locations of suppliers and DC’s, the assignment of each location-fixed DC to a supplier and that of each retailer to a DC, which minimizes the system-wide location, transportation, and inventory costs. The problem is formulated as a nonlinear integer programming model, for which a two-phase heuristic solution algorithm is derived based on the Lagrangian relaxation approach. Numerical experiments show that the proposed heuristic is effective and also efficient.     

Determinants of route choice behavior: A comparison of shop versus work trips using the Potential Path Area - Gateway (PPAG) algorithm and Path-Size Logit

This paper presents an in-depth comparison of route choice models for work and shop vehicle trips—with emphasis on the interactions between route attributes and individual characteristics—to better understand the route choice determinants that are assumed to vary by trip purpose. Insights into the route choice behavior involving two dominant vehicle trip purposes—work and shop trips—will help in the design of traffic facilities and implementation of measures to influence route choice in the desired direction.In this study, we show that the utility and scale parameters for separate models of work and shop trips differ by direct comparison using a sequential scaling estimation method and likelihood ratio tests, and highlight the differences in route choice behavior by considering the interaction of route attributes and individual characteristics using Path-Size Logit modeling. In the process, we used Potential Path Area - Gateway (PPAG) algorithm—that generates feasible route choice sets for route choice modeling from GPS trajectories of observed routes.The results show that, indeed, route choice behavior varies by trip, which suggests that drivers attach value to route choice determinants relative to trip purpose. The inclusion of interaction terms in model specifications further indicates that work route choice behavior tends to be restrictive compared to the nonrestrictive route choice for shop trips—a generalization consistent with the mandatory and discretionary nature of work and shop trips, respectively. Specifically, individual characteristics such as personal income, age, gender, tenure, household size, and access to public transit affect route choice behavior.     

Car-sharing organizations: The size of the market segment and revealed change in mobility behavior

Car-sharing organizations (CSO) have recently spread throughout central European cities and currently have 20000 members. They lower individual fixed costs of car availability change the incentive structure of private vehicle use by transforming nearly all costs into variable costs. A survey of all current Austrian CSO members is used to identify the characteristics significant of members. A procedure is proposed to quantify urban local market segment potentials and is applied to two residential areas. The net impact of CSOs depends on how the new incentive structure changes mobility behavior. A controlled experiment of voluntary new members was carried out to compare pre-membership and membership trip structure and modal split. Results indicate a substantial reduction of aggregate private vehicle mileage. While the share of trips by car is constant, changes in trip length are observed, with there being different changes for households which previously owned a car and those which did not. Combining behavior impact with market segment size results in the quantification of emission reduction and car ownership reduction (land use demand) due to car-sharing, which is a decentralized demand-side transport policy.     

Optimization approach to depot location and trip selection in one-way carsharing systems

In this paper, we present an optimization approach to depot location in one-way carsharing systems where vehicle stock imbalance issues are addressed under three trip selection schemes. The approach is based on mixed-integer programming models whose objective is to maximize the profits of a carsharing organization considering all the revenues and costs involved. The practical usefulness of the approach is illustrated with a case study involving the municipality of Lisbon, Portugal. The results we have obtained from this study provided a clear insight into the impact of depot location and trip selection schemes on the profitability of such systems.     

Differentiating metropolitan transport disadvantage by mode: Household expenditure on private vehicle fuel and public transport fares in Brisbane,Australia

Public transport (PT) has become important in everyday travels in Australian cities. Rising PT fares create a competitive disadvantage against private motor vehicles which is threatening PT ridership. This paper seeks to gain further insights into transport disadvantage by exploring spatial patterns of household transport expenditure on PT fares and private vehicle fuel use for the Brisbane metropolitan area. Several datasets are used to measure mode-specific transport costs, including the journey to work matrix, fuel efficiency of the private vehicle fleet and PT fares for the city. Through an advanced spatial analysis, the results show that PT was not a cost-effective means of transport for households when compared to private motor vehicles. The paper then compares mode-specific trip costs with patterns of suburban socio-economic disadvantage in Brisbane. We demonstrate that the high PT fares increase household exposure to higher transport costs and compound other forms of transport disadvantage and vulnerability, particularly in outer suburban areas.     

A hybrid population heuristic for the heterogeneous vehicle routing problems

The heterogeneous vehicle routing problem (HVRP) plays an important role in supply chain logistics. Two variants of HVRP are treated in this paper: one with fixed and variable costs (HVRPFD), and the other with only variable cost (HVRPD). A hybrid population heuristic that is able to solve both variants is proposed, in which a population of solutions are progressively evolved by crossovers and local searches. Computational results on a set of eight benchmark test problems from literature show that the proposed heuristic produces excellent solutions in short computing times.     

Green accessibility: Estimating the environmental costs of network-time prisms for sustainable transportation planning

Accessibility, or the ease to participate in activities and obtain resources in a given environment, is crucial for evaluating transportation systems. Greater accessibility is often achieved by increasing individuals' potential mobility. However, potential mobility, if realized by motorized modes, can also generate negative environmental impacts such as fossil fuel consumption and greenhouse gas (GHG) emissions. While the negative environmental impacts of greater mobility are acknowledged, there has been a lack of research to validate those impacts using empirical data, especially considering variations in individuals' mobility levels. This paper presents a method for estimating the expected environmental costs of accessibility represented by a network-time prism (NTP). A NTP delimits all accessible locations within a network and the available time for an individual to present at each location given a scheduled trip origin and destination, a time budget and the maximum achievable speeds along network edges. Estimating the expected environmental costs of a NTP involves three steps: (1) semi-Markov techniques to simulate the probabilities to move along network edges at given times; (2) the speed profiles for reachable edges, and (3) a cost function that translates speeds into environmental impacts. We focus on air quality and employ the motor vehicle emission simulator MOVESLite to estimate the CO₂ emissions at both the edge and prism levels. We calibrate and validate the methods for experimental NTPs defined within the Phoenix, AZ, USA road and highway network using vehicles instrumented with GPS-enabled onboard diagnostic devices (OBD). We demonstrate the effectiveness of our method through two scenarios and investigate the impact of changes in mobility levels on the expected CO₂ emissions associated with the experimental NTPs.     

Measuring housing and transportation affordability: A case study of Melbourne,Australia

Housing affordability is traditionally measured using the percentage of household income spent on housing. An important cost that is usually overlooked in measuring location affordability is the transportation or accessibility costs. In this paper, we present a modeling approach, driven by urban open data, to measure location affordability that incorporates both housing and transportation costs. We apply the developed model to assess housing affordability in Melbourne, Australia as a case study. Results suggest that neighbourhoods that appear to be affordable when only housing cost is considered are not necessarily affordable when transportation costs are taken into account. A negative correlation between housing affordability and transportation affordability is observed. We also identify the presence of a strong spatial clustering pattern in the affordability measure across the study area. A major methodological contribution of the paper is the inclusion of comprehensive private vehicle costs and public transportation expenses in the model that contributes to a more robust estimation and understanding of location affordability. The model also distinguishes between different trip purposes. Results suggest that plans and policies to improve housing affordability should be made in coordination with transportation infrastructure investment plans to ensure effective and equitable outcomes. Nevertheless, the focus of the paper is more on the measurement of affordability; rather than reviewing and recommending housing related policies.     

Aircraft line maintenance scheduling and optimisation

With the advent of new technologies and more modern aircraft, many of the maintenance jobs traditionally scheduled for periodic block checks can now be performed in the ‘‘line maintenance” environment, i.e., during layovers between scheduled flights of an aircraft. This flexibility can be exploited to reduce maintenance costs and improve fleet utilisation of an airline. In this paper we introduce and study the Line Maintenance Scheduling Problem (LMSP). The LMSP assigns jobs to available maintenance opportunities, defined by aircraft routes, and sets the starting time for each job. Its objective is to minimise the deviation from this schedule with respect to given due dates for each task, without exceeding resource capacity at the airports at any moment. We formulate the LMSP as a mixed integer programming problem, and describe and compare two solution approaches for this problem: an integrated exact solution algorithm, which solves job assignment and timetabling simultaneously, and a sequential, heuristic approach. We tested our algorithms on a set of instances inspired on data provided by an industry partner. Our experiments show the applicability of both approaches on realistic settings: the exact approach was able to find the optimal solution for all instances, in less than 10 min on average. Our analysis also shows with an example that line maintenance can be more efficient when capacity is spatially spread, even if the total capacity is reduced.     

Congestion and multimodal transport: a survey of cargo transport operators in the Netherlands

Longer and more frequent traffic jams in the Netherlands are increasing the costs of transporting cargo. Tightly scheduled production systems rely on punctual materials movements, but are congestion-induced delays sufficient to stimulate freight mode switching from road to combined road–rail and road–water movements? A survey of Dutch transport companies revealed an estimated 10% of vehicle operating time spent in congested conditions. The perceived impact on transport operations, consumers and service characteristics are reported. Based on the survey findings, a vehicle cost simulation attributed 7% of transport costs to congestion, increasing the attractiveness of multimodal transport and other solutions.     

Incorporating inventory control decisions into a strategic distribution network design model with stochastic demand

In this paper, we propose a simultaneous approach to incorporate inventory control decisions––such as economic order quantity and safety stock decisions––into typical facility location models, which are used to solve the distribution network design problem. A simultaneous model is developed considering a stochastic demand, modeling also the risk pooling phenomenon. We present a non-linear-mixed-integer model and a heuristic solution approach, based on Lagrangian relaxation and the sub-gradient method. In a numerical application, we found that the potential cost reduction, compared to the traditional approach, increases when the holding costs and/or the variability of demand are higher.     

Credit-based congestion pricing: A Dallas-Fort Worth application

Under a credit-based congestion pricing policy, net revenues are distributed uniformly among qualifying travelers, to partially offset toll payments. This work predicts the traffic impacts, air-quality changes, welfare effects, and system implementation costs of such a policy, as applied to the Dallas-Fort Worth (DFW) region of Texas. Joint destination-mode choice models were estimated and applied. The status quo and two marginal cost pricing (MCP) scenarios were simulated for the short and long terms, with full feedback of trip costs and times. Monetarized logsum differences suggest that marginal cost pricing of congested freeways in this urban region, followed by travel credit distribution to all workers, is welfare improving for the great majority of such travelers. Moreover, high levels of recurring congestion (V/C ratios exceeding 1.5) are predicted to practically disappear.     

How thick is the border: the relative cost of Canadian domestic and cross-border truck-borne trade, 2004–2009

Despite the elimination of tariff barriers between Canada and the United States, the volume of trade between the two countries is less than would be expected in the absence of impediments. While considerable work has been done to gauge the degree of integration between the Canadian and U.S. economies through trade, relatively little analysis has parsed out the underlying costs of the border. The costs of crossing the border can be divided into formal tariff barriers, non-tariff barriers, and the cost of the transport system. This paper focuses on the latter by estimating the cost of shipping goods by truck between Canada and the U.S. during the 2004–2009 period. The incremental cost of import and export over domestic shipments is measured in both absolute and ad valorem terms. The latter provides an estimate of the border increment in transportation cost as a tariff equivalent. The incremental cost is further broken down into fixed and variable (line-haul) components. Higher fixed costs are consistent with border delays and border compliance costs being passed on to the consumers of trucking services. Higher line-haul costs may result from difficulties obtaining backhauls for a portion of the trip home, which may stem from trade imbalances and regulations that restrict the ability of Canadian-based carriers to transport goods between two points in the U.S.     

The split delivery vehicle routing problem with minimum delivery amounts

In the vehicle routing problem, a fleet of vehicles must service the demands of customers in a least-cost way. By allowing multiple vehicles to service the same customer (i.e., splitting deliveries), substantial savings in travel costs are possible. However, split deliveries are often an inconvenience to the customer who would prefer to have demand serviced in a single visit. We consider the vehicle routing problem in which split deliveries are allowed only if a minimum fraction of a customer’s demand is serviced by a vehicle. We develop a heuristic method for solving this problem and report computational results on a wide range of problem sets.     

Comparing the p-median and flow-refueling models for locating alternative-fuel stations

The p-median and flow-refueling models are two of the more popular models for optimal location of alternative-fuel stations. The p-median model, one of the most widely used location models of any kind, locates p facilities and allocates demand nodes to them to minimize total weighted distance traveled. In comparison, the flow-refueling location model (FRLM) is a path-based demand model that locates p stations to maximize the number of trips on their shortest paths that can be refueled. For a path to be considered refuelable, one or more stations must be located on the path in a way that allows the round trip to be completed without running out of fuel, given the vehicle driving range. In this paper, we analyze how well the facilities located by each model perform on the other’s objective function on road networks in Florida. While each objective function degrades somewhat when facilities are located by the other model, the stations located by the flow-refueling model generally do better on the p-median objective than the stations located by the p-median model do on the flow-refueling objective. This difference between the two models is even more pronounced at the state scale than at the metropolitan scale. In addition, the optimal locations for the FRLM tend to be more much more stable as p increases than those located by the p-median model.     

Willingness to pay for travel time reliability in passenger transport: A review and some new empirical evidence

This paper reviews and critiques the modelling frameworks and empirical measurement paradigms used to obtain willingness to pay (WTP) for improved travel time reliability, suggesting new directions for ongoing research. We also estimate models to derive values of reliability, scheduling costs and reliability ratios in the context of Australian toll roads and use the new evidence to highlight the important influence of the way that trip time variability is included in stated preference studies in deriving WTP estimates of reliability in absolute terms, and relative to the value of travel time savings.     

A carrier’s optimal bid generation problem in combinatorial auctions for transportation procurement

We consider the carrier’s optimal bid generation problem in combinatorial auctions for transportation procurement. Bidders (carriers) employ vehicle routing models to identify sets of lanes (origin-destination pairs) based on the actual routes that a fleet of trucks will follow in order to maximize profit. Routes are constructed by optimally trading off repositioning costs of vehicles and the rewards associated with servicing lanes. The carrier optimization represents simultaneous generation and selection of routes and can incorporate any existing commitment. We employ both column generation and Lagrangian based techniques for solving the carrier optimization model and present numerical results.     

The multi-period service territory design problem – An introduction,a model and a heuristic approach

In service territory design applications, a field service workforce is responsible for providing recurring services at their customers’ sites. We introduce the associated planning problem, which consists of two subproblems: In the partitioning subproblem, customers must be grouped into service territories. In the scheduling subproblem, customer visits must be scheduled throughout the multi-period planning horizon. The emphasis of this paper is put on the scheduling subproblem. We propose a mixed integer programming model for this subproblem and present a location-allocation heuristic. The results of extensive experiments on real-world instances show that the proposed heuristic produces high-quality solutions.     

Analysis of the potential demand for battery electric vehicle sharing: Mode share and spatiotemporal distribution

Carsharing is considered one of the solutions to urban transport problems. As a new mode in the urban transport system in China, there are still initial questions of how carsharing will perform and what the impacts will be. Accordingly, this study considers battery electric vehicle sharing and investigates its potential demand, with Beijing as the case study. A nested logit model is established and calibrated to analyze mode choice behavior. Further, real trip data is used to estimate the potential demand for battery electric vehicle sharing. In addition, the temporal and spatial distribution of potential demand, the impact of battery electric vehicle sharing on the mode split, and the impact of pricing strategies are analyzed. The results show that an optimistic mode split of battery electric vehicle sharing is 4.23% when the average distance between travelers and stations is 0.5 km. The main source of potential demand is public transport. However, the substitution effect of battery electric vehicle sharing for private vehicles is weak. The potential trips are concentrated in the morning peak period, mainly starting in residential or integrative areas, and ending in commercial areas or green spaces. Commuting and long-distance trips are more sensitive to decreases in price, such that they are more likely to be completed as battery electric vehicle sharing trips. This price decrease could also increase the potential trip ratio during the evening peak period. These findings are useful to governments and operators for implementing policies such as station planning, relocation, and pricing strategies.