Search

In this paper we present the solution to a weekly log-truck scheduling problem (LTSP) integrating the routing and scheduling of trucks where all goods are transported in full truckloads. We must take into account pick-up and delivery requirements, multiple products, inventory levels, and lunch breaks. The objective is to minimize the overall transportation cost including wait times and the empty and loaded distance traveled. Our solution is based on a two-phase approach. The first phase involves an integer linear program that determines the destinations of full truckloads. The second phase uses an implicit integer linear program based on an arc formulation to ensure that the trucks are routed and scheduled at a minimum cost. Experiments have been conducted using Cplex 12.4.0, and almost all instances were solved within six hours with a reasonable gap. [ABSTRACT FROM AUTHOR]

This paper deals with uncapacitated single and multiple allocation p-hub maximal covering problems (USApHMCP and UMApHMCP) with binary and partial covering criteria. We present new mixed-integer programming formulations of the considered problems, which are valid for both binary and partial coverage cases. The efficiency of the proposed formulations is evaluated through computational experiments on smaller-size instances, and compared with the state-of-the art models from the literature. The obtained results indicate that the new UMApHMCP formulation outperforms the existing one for both coverage criteria in the sense of solutions' quality and running times. In order to solve instances of larger problem dimension, we develop two heuristic methods based on variable neighborhood search: general VNS (GVNS) for USApHMCP and basic VNS (BVNS) for UMApHMCP. The proposed GVNS and BVNS involve the same shaking procedure in order to hopefully escape local minima traps, while local search phases in GVNS and BVNS use different neighborhood structures in accordance with applied allocation schemes. Computational experiments conducted on smaller-size instances showed that both GVNS and BVNS almost instantly reach all known optimal solutions. In addition, the proposed GVNS and BVNS showed to be very efficient when solving large and large-scale hub instances with up to 1000 nodes, which were not previously considered as test instances for the considered problems. Both GVNS and BVNS provided best solutions on challenging USApHMCP and UMApHMCP instances for both coverage cases in short running times, which indicates their potential to be applied to similar problems. [ABSTRACT FROM AUTHOR]

This study considers a combination of strategic and tactical levels of operating room planning where two types of full-day and half-day blocks are considered. Constraints on available beds in hospital wards and different durations of stay for elective patients in the ward are the main assumptions of the problem. The aim is to minimize overtime and idleness of operating rooms, maximize surgeons' satisfaction and minimize the number of unscheduled surgeries in the master surgery schedule. We propose a mixed integer programming model as well as a novel heuristic algorithm by combining simulated annealing meta-heuristic and linear programming models. Real data from a teaching-educational hospital with 20 operating rooms and 47 surgeons' groups as well as some random problem instances are used in the experiments. The results indicate high performance of the proposed heuristic algorithm in generating near-optimal Pareto solutions compared with the mathematical model and a local search algorithm from the literature. Sensitivity analysis is done on some parameters of the problem like overtime cost of operating rooms, maximum allowable overtime, available beds in the ward, and the number of attendance days preferred by each surgeon. The results from our case study show that 6% of operating room costs are related to the fact that some surgeons are unwilling to perform surgeries on some days of a week. Also, adding 20% to the capacity of ward beds results in 3% and 10% decrease in unscheduled surgeries and operating rooms idleness, respectively. [ABSTRACT FROM AUTHOR]