Reachability cuts for the vehicle routing problem with time windows

This paper introduces a class of cuts, called reachability cuts, for the Vehicle Routing Problem with Time Windows (VRPTW). Reachability cuts are closely related to cuts derived from precedence constraints in the Asymmetric Traveling Salesman Problem with Time Windows and to k-path cuts for the VRPTW. In particular, any reachability cut dominates one or more k-path cuts. The paper presents separation procedures for reachability cuts and reports computational experiments on well-known VRPTW instances. The computational results suggest that reachability cuts can be highly useful as cutting planes for certain VRPTW instances.Routing; time windows; precedence constraints

Optimal scheduling for refueling multiple autonomous aerial vehicles

The scheduling, for autonomous refueling, of multiple unmanned aerial vehicles (UAVs) is posed as a combinatorial optimization problem. An efficient dynamic programming (DP) algorithm is introduced for finding the optimal initial refueling sequence. The optimal sequence needs to be recalculated when conditions change, such as when UAVs join or leave the queue unexpectedly. We develop a systematic shuffle scheme to reconfigure the UAV sequence using the least amount of shuffle steps. A similarity metric over UAV sequences is introduced to quantify the reconfiguration effort which is treated as an additional cost and is integrated into the DP algorithm. Feasibility and limitations of this novel approach are also discussed

On Alternative Formulations to the Shortest Path Problem with Time Windows and Capacity Constraints

The elementary shortest-path problem with time-windows and capac-ity constraints is a problem used for solving vehicle-routing and crew-scheduling applications. It occurs as a sub-problem used to implicitly generate the set of all feasible routes and schedules in the column-generation formulation of the vehicle routing problem with time windows and its variations. In the problem there is a directed graph with a source node and a destination node, and each arc has a cost and a vector of weights specifying its requirements of a resource with a finite capacity. A minimum cost source–destination directed path is sought such that the total consumption of the resource does not exceed the capacity. The problem ins NP-hard in the strong sense. We review integer-linear formulation to the problem and compare them in order to study their computational efficiency.Sociedad Argentina de Informática e Investigación Operativ

On Alternative Formulations to the Shortest Path Problem with Time Windows and Capacity Constraints

The elementary shortest-path problem with time-windows and capac-ity constraints is a problem used for solving vehicle-routing and crew-scheduling applications. It occurs as a sub-problem used to implicitly generate the set of all feasible routes and schedules in the column-generation formulation of the vehicle routing problem with time windows and its variations. In the problem there is a directed graph with a source node and a destination node, and each arc has a cost and a vector of weights specifying its requirements of a resource with a finite capacity. A minimum cost source–destination directed path is sought such that the total consumption of the resource does not exceed the capacity. The problem ins NP-hard in the strong sense. We review integer-linear formulation to the problem and compare them in order to study their computational efficiency.Sociedad Argentina de Informática e Investigación Operativ

On Alternative Formulations to the Shortest Path Problem with Time Windows and Capacity Constraints

The elementary shortest-path problem with time-windows and capac-ity constraints is a problem used for solving vehicle-routing and crew-scheduling applications. It occurs as a sub-problem used to implicitly generate the set of all feasible routes and schedules in the column-generation formulation of the vehicle routing problem with time windows and its variations. In the problem there is a directed graph with a source node and a destination node, and each arc has a cost and a vector of weights specifying its requirements of a resource with a finite capacity. A minimum cost source–destination directed path is sought such that the total consumption of the resource does not exceed the capacity. The problem ins NP-hard in the strong sense. We review integer-linear formulation to the problem and compare them in order to study their computational efficiency.Sociedad Argentina de Informática e Investigación Operativ

A dynamic lot-sizing model with demand time windows

One of the basic assumptions of the classical dynamic lot-sizing model is that the aggregate demand of a given period must be satisfied in that period. Under this assumption, if backlogging is not allowed then the demand of a given period cannot be delivered earlier or later than the period. If backlogging is allowed, the demand of a given period cannot be delivered earlier than the period, but can be delivered later at the expense of a backordering cost. Like most mathematical models, the classical dynamic lot-sizing model is a simplified paraphrase of what might actually happen in real life. In most real life applications, the customer offers a grace period - we call it a demand time window - during which a particular demand can be satisfied with no penalty. That is, in association with each demand, the customer specifies an earliest and a latest delivery time. The time interval characterized by the earliest and latest delivery dates of a demand represents the corresponding time window. This paper studies the dynamic lot-sizing problem with demand time windows and provides polynomial time algorithms for computing its solution. If shortages are not allowed, the complexity of the proposed algorithm is of the order T square. When backlogging is allowed, the complexity of the proposed algorithm is of the order T cube.dynamic programming;lot-sizing;time windows

The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling

Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhanced Swift Converging Simulated Annealing (ESCSA) algorithm, to solve the complex real-time scheduling problems. The proposed algorithm inherits the prominent features of the Genetic Algorithm (GA), Simulated Annealing (SA), and the Fuzzy Logic Controller (FLC). The ESCSA algorithm reduces the makespan significantly in less computational time and number of iterations. The efficacy of the proposed algorithm has been shown by comparing the results with GA, SA, Tabu, and hybrid Tabu-SA optimization methods

Cargo consolidation and distribution through a terminals-network : A branch-and-price approach

Less-than-truckload (LTL) is a transport modality that includes many practical variations to convey a number of transportation-requests from the origin locations to their destinations by using the possibility of goodstransshipments on the carrier’s terminals-network. In this way logistics companies are required to consolidate shipments from different suppliers in the outbound vehicles at a terminal of the network. We present a methodology for finding near-optimal solutions to a LTL shipping modality used for cargo consolidation and distribution through a terminals-network. The methodology uses column generation combined with an incomplete branch-and-price procedure.Sociedad Argentina de Informática e Investigación Operativa (SADIO