00983321

Component

https://doi.org/10.3141/1882-20

http://scholar.google.com...hani&publication_year=2004

The present research deals with a special case of emergency truck routing for snow removal or salting (snow routing) in which the objective function is primarily to minimize the number of trucks and secondarily to minimize the number of deadhead miles while the snow network is salted as much as required and the trucks' salting capacity is not violated. An additional constraint requires each truck service route to be a connected network. This route continuity constraint helps avoid confusion for truck drivers. A three-phase approach to the problem is presented: first, minimize the number of trucks; second, balance the workloads; and third, find the best routes to minimize the number of deadhead miles. The minimal arc partitioning problem (MAP) is introduced as an abstraction of the first phase (minimization of the number of trucks). MAP is stated as determination of the minimal arc partitioning of a network so that each partition (subnetwork) constitutes a connected network and so that capacity constraints are satisfied. Balancing the trucks and routing them to each subnetwork are dealt with in the other phases. The approach is applied to a real-world snow emergency network, and the results are discussed. It is demonstrated that the number of trucks can be reduced by up to 15% and the number of deadhead miles can be reduced by up to 70% compared with the number of trucks and the number of deadhead miles with the current plan. In addition, the overall algorithm is quite fast.

This paper appears in Transportation Research Record No. 1882, Transportation Network Modeling 2004.

00983301

English

p. 167-175

2004

Transportation Research Record

0309094755

Figures (3) ; References (19) ; Tables (2)

Algorithms; Deadheading; Deicing; Minimization; Routing; Snow removal; Trucks; Workload

Minimal arc partitioning

Highways; Maintenance and Preservation; Motor Carriers; Planning and Forecasting; I62: Winter Maintenance; I72: Traffic and Transport Planning

TRIS, TRB

Dec 15 2004 12:00AM

• APPLYING A NETWORK PROGRAMMING ALGORITHM TO A NETWORKWIDE TRAFFIC CONTROL SCHEME: SIMULATION-BASED PERFORMANCE STUDIES
• APPROXIMATE PROCEDURES FOR PROBABILISTIC TRAVELING SALESPERSON PROBLEM
• COMBINATORIAL APPROACH FOR MULTIPLE-DESTINATION USER OPTIMAL DYNAMIC TRAFFIC ASSIGNMENT
• COMPETITIVE PERFORMANCE ASSESSMENT OF DYNAMIC VEHICLE ROUTING TECHNOLOGIES USING SEQUENTIAL AUCTIONS
• DYNAMIC ROUTING DECISIONS FOR COMMERCIAL VEHICLE OPERATIONS IN REAL-TIME TRAFFIC CONDITIONS
• DYNAMIC TRUCKLOAD ROUTING, SCHEDULING, AND LOAD ACCEPTANCE
• ENHANCED DYNAMIC ORIGIN-DESTINATION MATRIX UPDATING WITH LONG-TERM FLOW INFORMATION
• ESTIMATION OF TURNING MOVEMENTS AT INTERSECTIONS: JOINT TRIP DISTRIBUTION AND TRAFFIC ASSIGNMENT PROGRAM COMBINED WITH A GENETIC ALGORITHM
• FORMULATION OF ANALYTICAL TIME-VARYING INTERMODAL PERSON TRIP ASSIGNMENT MODEL
• INCORPORATING AUTOMATED VEHICLE IDENTIFICATION DATA INTO ORIGIN-DESTINATION ESTIMATION
• INTEGRATED APPROACH FOR EMERGENCY MEDICAL SERVICE LOCATION AND ASSIGNMENT PROBLEM
• METHODOLOGY FOR DETERMINING VULNERABLE LINKS IN A TRANSPORTATION NETWORK
• MODELING REPEATED MULTINOMIAL ROUTE CHOICES UNDER ADVANCED TRAVELER INFORMATION SYSTEM: GENERALIZED ESTIMATING EQUATIONS WITH POLYTOMOUS LOGIT FUNCTION
• MULTIDEPOT VEHICLE ROUTING WITH UNCERTAIN DEMANDS: CHANCE CONSTRAINED APPROACH
• OPTIMAL TOLLS WITH A MULTICLASS, BICRITERION TRAFFIC NETWORK EQUILIBRIUM
• PREDICTING INTERNATIONAL FREIGHT FLOWS FOR TRADE: SIMULTANEOUS MULTIMODAL, MULTICOMMODITY, NETWORK EQUILIBRIUM MODEL
• SEQUENTIAL LOGIT DYNAMIC TRAVEL DEMAND MODEL FOR HURRICANE EVACUATION
• SIMULATION MODEL FOR REAL-TIME EMERGENCY VEHICLE DISPATCHING AND ROUTING
• STOCHASTIC TRANSPORTATION NETWORK DESIGN PROBLEM WITH SPATIAL EQUITY CONSTRAINT
• TABU SEARCH ALGORITHM FOR DYNAMIC VEHICLE ROUTING PROBLEMS UNDER REAL-TIME INFORMATION
• TAXI DISPATCH SYSTEM BASED ON CURRENT DEMANDS AND REAL-TIME TRAFFIC CONDITIONS
• TRANSPORTATION NETWORK OPTIMIZATION PROBLEMS WITH STOCHASTIC USER EQUILIBRIUM CONSTRAINTS
• VEHICLE ROUTING AND SCHEDULING PROBLEM WITH TIME WINDOWS AND STOCHASTIC DEMAND