Branch and Cut and Price for the Pickup and Delivery Problem with Time Windows
Transportation Science
Path-Reduced Costs for Eliminating Arcs in Routing and Scheduling
INFORMS Journal on Computing
INFORMS Journal on Computing
Enhanced Branch and Price and Cut for Vehicle Routing with Split Deliveries and Time Windows
Transportation Science
New Route Relaxation and Pricing Strategies for the Vehicle Routing Problem
Operations Research
New State-Space Relaxations for Solving the Traveling Salesman Problem with Time Windows
INFORMS Journal on Computing
Vehicle routing problem with stochastic travel times including soft time windows and service costs
Computers and Operations Research
Hybrid column generation and large neighborhood search for the dial-a-ride problem
Computers and Operations Research
Cut-First Branch-and-Price-Second for the Capacitated Arc-Routing Problem
Operations Research
Lifted and Local Reachability Cuts for the Vehicle Routing Problem with Time Windows
Computers and Operations Research
Using the primal-dual interior point algorithm within the branch-price-and-cut method
Computers and Operations Research
Branch and Price for the Time-Dependent Vehicle Routing Problem with Time Windows
Transportation Science
Combined location and routing problems for drug distribution
Discrete Applied Mathematics
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The vehicle routing problem with time windows consists of delivering goods at minimum cost to a set of customers using an unlimited number of capacitated vehicles assigned to a single depot. Each customer must be visited within a prescribed time window. The most recent successful solution methods for this problem are branch-and-price-and-cut algorithms where the column generation subproblem is an elementary shortest-path problem with resource constraints (ESPPRC). In this paper, we propose new ideas having the potential to improve such a methodology. First, we develop a tabu search heuristic for the ESPPRC that allows, in most iterations, the generation of negative reduced cost columns in a short computation time. Second, to further accelerate the subproblem solution process, we propose to relax the elementarity requirements for a subset of the nodes. This relaxation, however, yields weaker lower bounds. Third, we introduce a generalization of the k-path inequalities and highlight that these generalized inequalities can, in theory, be stronger than the traditional ones. Finally, combining these ideas with the most recent advances published in the literature, we present a wide variety of computational results on the Solomon's 100-customer benchmark instances. In particular, we report solving five previously unsolved instances.