Author
Emilio Zamorano
Bio: Emilio Zamorano is an academic researcher from University of Mannheim. The author has contributed to research in topics: Job shop scheduling & Dynamic priority scheduling. The author has an hindex of 3, co-authored 3 publications receiving 75 citations.
Papers
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TL;DR: This paper proposes a mixed integer program and a branch-and-price algorithm to solve a technician routing and scheduling problem motivated by the case of an external maintenance provider.
74 citations
TL;DR: In this article, the authors present an optimization model for the tour scheduling problem for agents with multiple skills and flexible contracts in check-in counters at airports, where the objective is to minimize the total assignment costs subject to demand fulfillment and labor regulations.
Abstract: This paper presents an optimization model for the tour scheduling problem for agents with multiple skills and flexible contracts in check-in counters at airports. The objective is to minimize the total assignment costs subject to demand fulfillment and labor regulations. In order to solve this problem we develop a rolling planning horizon-based heuristic. Our heuristic is robust and provides near-optimal schedules within reasonable computation time for real-world cases, although the parameter selection is important to its performance. In addition, we discuss the impact of the skill distribution on the scheduling costs for several instances.
20 citations
TL;DR: A mixed-integer program and a branch-and-price algorithm are proposed to solve the task assignment problem encountered by check-in counter personnel at airports by exploiting the problem structure to efficiently formulate the pricing problems and improve computation time.
Abstract: This paper addresses a task assignment problem encountered by check-in counter personnel at airports. The problem consists of assigning multiskilled agents to a sequence of tasks in check-in counters. Because each task’s ending time is fixed to comply with the flight schedule, its processing time depends on the arrival of the assigned agents. We propose a mixed-integer program and a branch-and-price algorithm to solve this problem. We exploit the problem structure to efficiently formulate the pricing problems and improve computation time. Using real-world data from a German ground-handling agency, we conduct numerical studies to evaluate the performance of the proposed solutions.
6 citations
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TL;DR: In this article, an enhanced artificial bee colony (EABC) algorithm and a route truncation heuristic are jointly used to optimize the route design in each stage, and the loading and unloading sub-problem along the route in a given stage.
Abstract: This paper introduces a new dynamic green bike repositioning problem (DGBRP) that simultaneously minimizes the total unmet demand of the bike-sharing system and the fuel and CO 2 emission cost of the repositioning vehicle over an operational period. The problem determines the route and the number of bikes loaded and unloaded at each visited node over a multi-period operational horizon during which the cycling demand at each node varies from time to time. To handle the dynamic nature of the problem, this study adopts a rolling horizon approach to break down the proposed problem into a set of stages, in which a static bike repositioning sub-problem is solved in each stage. An enhanced artificial bee colony (EABC) algorithm and a route truncation heuristic are jointly used to optimize the route design in each stage, and the loading and unloading heuristic is used to tackle the loading and unloading sub-problem along the route in a given stage. Numerical results show that the EABC algorithm outperforms Genetic Algorithm in solving the routing sub-problem. Computation experiments are performed to illustrate the effect of the stage duration on the two objective values, and the results show that longer stage duration leads to higher total unmet demand and total fuel and CO 2 emission cost. Numerical studies are also performed to illustrate the effects of the weight and the loading and unloading times on the two objective values and the tradeoff between the two objectives.
97 citations
TL;DR: This study investigates a tug-scheduling problem at a seaport that is located at a river mouth and that connects the hinterland ports along the river with the global maritime transportation network using a mixed-integer programming model.
45 citations
TL;DR: This is first time in the literature that a research observes bi-objective model of preventive maintenance planning in geographically dispersed systems through prognostic information and Remaining Useful Life (RUL) and the results demonstrate the capability of the newly introduced model.
44 citations
TL;DR: In this paper, the authors present an optimization method for the aircraft scheduling problem with general runway configurations, where take-offs and landings have to be assigned to a runway and a time while meeting the sequence-dependent separation requirements and minimizing the costs incurred by delays.
Abstract: This paper presents an optimization method for the aircraft scheduling problem with general runway configurations. Take-offs and landings have to be assigned to a runway and a time while meeting the sequence-dependent separation requirements and minimizing the costs incurred by delays. Some runways can be used only for take-offs, landings, or certain types of aircraft while schedules for interdependent runways have to consider additional diagonal separation constraints.Our dynamic programming approach solves realistic problem instances to optimality within short computation times. In addition, we propose a rolling planning horizon heuristic for large instances that returns close-to-optimal results.
44 citations
TL;DR: In this paper, an optimization method for the aircraft scheduling problem with general runway configurations is presented, where take-offs and landings have to be assigned to a runway and a time while meeting the sequence-dependent separation requirements and minimizing the costs incurred by delays.
Abstract: This paper presents an optimization method for the aircraft scheduling problem with general runway configurations. Take-offs and landings have to be assigned to a runway and a time while meeting the sequence-dependent separation requirements and minimizing the costs incurred by delays. Some runways can be used only for take-offs, landings, or certain types of aircraft while schedules for interdependent runways have to consider additional diagonal separation constraints.
Our dynamic programming approach solves realistic problem instances to optimality within short computation times. In addition, we propose a rolling planning horizon heuristic for large instances that returns close-to-optimal results.
42 citations