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The problem of determining a schedule of jobs with unit-time lengths on a single machine that minimizes the total weighted earliness and tardiness penalties with respect to arbitrary rational due-dates is formulated as an integer programming problem. We show that if the penalties meet a certain criterion, called the Dominance Condition, then there exists an(More)
We consider the Multiple Vehicle Pickup and Delivery Problem (MVPDP) with objective of minimizing the total travel cost and the fixed vehicle cost. Most of the optimization based approaches for solving the MVPDP are developed for a restrictive hard time window or tight capacity environment that depend significantly on the reduction of the feasible solution(More)
Trains operating in densely populated metropolitan areas typically encounter complex trackage configurations. To make optimal use of the available rail capacity, some portions of the rail network may consist of single-track lines while other locations may consist of double- or triple-track lines. Because of varying local conditions, different points in the(More)
This paper investigates the construction of routes for local delivery of packages. The primary objective of this research is to provide realistic models to optimize vehicle dispatching when customer locations and demands vary from day to day, while maintaining driver familiarity with their service territories, hence dispatch consistency. The objective of(More)
We consider the Courier Delivery Problem, a variant of the Vehicle Routing Problem with time windows in which customers appear probabilistically and their service times are uncertain. We use scenario-based stochastic programming with recourse to model the uncertainty in customers and robust optimization for the uncertainty in service times. Our proposed(More)
M any real-world vehicle routing problems are dynamic optimization problems, with customer requests arriving over time, requiring a repeated reoptimization. In this paper, we consider a dynamic vehicle routing problem where one additional customer arrives at a beforehand unknown location when the vehicles are already under way. Our objective is to maximize(More)
In this paper, we propose models and solution approaches for determining the facility locations of medical supplies in response to large-scale emergencies. We address the demand uncertainty and medical supply insufficiency by providing each demand point with services from a multiple quantity of facilities that are located at different quality levels(More)
We introduce a new genetic algorithm (GA) approach for the integrated inventory distribution problem (IIDP). We present the developed genetic representation and use a randomized version of a previously developed construction heuristic to generate the initial random population. We design suitable crossover and mutation operators for the GA improvement phase.(More)
To route and schedule trains over a large complex network can be computationally intensive. One way to reduce complexity could be to " aggregate " suitable sections of a network. In this paper, we present a simulation-based technique to generate delay estimates over track segments as a function of traffic conditions, as well as network topology. We test our(More)