100 research outputs found
Bus driver rostering by hybrid methods based on column generation
Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2018Rostering problems arise in a diversity of areas where, according to the business and labor rules, distinct variants of the problem are obtained with different constraints and objectives considered. The diversity of existing rostering problems, allied with their complexity, justifies the activity of the research community addressing them. The current research on rostering problems is mainly devoted to achieving near-optimal solutions since, most of the times, the time needed to obtain optimal solutions is very high. In this thesis, a Bus Driver Rostering Problem is addressed, to which an integer programming model is adapted from the literature, and a new decomposition model with three distinct subproblems representations is proposed. The main objective of this research is to develop and evaluate a new approach to obtain solutions to the problem in study. The new approach follows the concept of search based on column generation, which consists in using the column generation method to solve problems represented by decomposition models and, after, applying metaheuristics to search for the best combination of subproblem solutions that, when combined, result in a feasible integer solution to the complete problem. Besides the new decomposition models proposed for the Bus Driver Rostering Problem, this thesis proposes the extension of the concept of search by column generation to allow using population-based metaheuristics and presents the implementation of the first metaheuristic using populations, based on the extension, which is an evolutionary algorithm. There are two additional contributions of this thesis. The first is an heuristic allowing to obtain solutions for the subproblems in an individual or aggregated way and the second is a repair operator which can be used by the metaheuristics to repair infeasible solutions and, eventually, generate missing subproblem solutions needed. The thesis includes the description and results from an extensive set of computational tests. Multiple configurations of the column generation with three decomposition models are tested to assess the best configuration to use in the generation of the search space for the metaheuristic. Additional tests compare distinct single-solution metaheuristics and our basic evolutionary algorithm in the search for integer solutions in the search space obtained by the column generation. A final set of tests compares the results of our final algorithm (with the best column generation configuration and the evolutionary algorithm using the repair operator) and the solutions obtained by solving the problem represented by the integer programming model with a commercial solver.Programa de Apoio à Formação Avançada de Docentes do Ensino Superior Politécnico (PROTEC), SFRH/PROTEC/67405/201
Solving Challenging Real-World Scheduling Problems
This work contains a series of studies on the optimization of three real-world scheduling problems, school timetabling, sports scheduling and staff scheduling. These challenging problems are solved to customer satisfaction using the proposed PEAST algorithm. The customer satisfaction refers to the fact that implementations of the algorithm are in industry use.
The PEAST algorithm is a product of long-term research and development. The first version of it was introduced in 1998. This thesis is a result of a five-year development of the algorithm. One of the most valuable characteristics of the algorithm has proven to be the ability to solve a wide range of scheduling problems. It is likely that it can be tuned to tackle also a range of other combinatorial problems.
The algorithm uses features from numerous different metaheuristics which is the main reason for its success. In addition, the implementation of the algorithm is fast enough for real-world use.Siirretty Doriast
Modeling the labor scheduling problem considering wellbeing for the clinic’s employees
Resumen
El problema de la programación de turnos de trabajo, consiste en programar el horario de trabajo o los turnos de los
distintos empleados buscando la minimización de los costos asociados al personal, el cual es un problema NP-hard.
En este artÃculo se presenta un modelo de programación lineal entera mixta aplicado a un caso real, el cual tiene
como objetivo minimizar el costo laboral, cumplir con los requerimientos de demanda y establecer condiciones
laborales adecuadas para los empleados mediante la incorporación de restricciones que garanticen bienestar, para
asà generar una asignación óptima de los turnos de trabajo de los fisioterapeutas en las áreas de cuidados intensivos e
intermedios de una ClÃnica. Para esto, se definieron diferentes escenarios variando tanto el número de fisioterapeutas
como la estructura del modelo, resultando asà que el número apropiado de fisioterapeutas a programar en la ClÃnica
es de 32, ya que satisface todos los requerimientos de demanda, la legislación laboral, y las necesidades de la
empresa y de los empleados. Abstract
The Labor Scheduling Problem consists of planning the shifts for the employees, and minimizing costs associated to
the workforce, which is a NP-hard problem.This paper presents a mixed integer linear programming modelapplied
to a real case, which minimizes labor costs, satisfies the requirements of demand and establishes adequate working
conditions for employees by incorporating constraints that ensure well-being to generate an optimal assignment
of physiotherapist shifts in the intensive and intermediate care areas in a Clinic.For this, different scenarios were
defined by varying both the number of physiotherapists and the structure of the model, the result that the appropriate
number of physiotherapists in the clinic schedule is 32, since it satisfies the requirements of demand, employment
law and the needs of the company and employees
The crew-scheduling module in the GIST system
The public transportation is gaining importance every year basically due the population growth, environmental policies and, route and street congestion. Too able an efficient management of all the resources related to public transportation, several techniques from different areas are being applied and several projects in Transportation Planning Systems, in different countries, are being developed. In this work, we present the GIST Planning Transportation Systems, a Portuguese project involving two universities and six public transportation companies. We describe in detail one of the most relevant modules of this project, the crew-scheduling module. The crew-scheduling module is based on the application of meta-heuristics, in particular GRASP, tabu search and genetic algorithm to solve the bus-driver-scheduling problem. The metaheuristics have been successfully incorporated in the GIST Planning Transportation Systems and are actually used by several companies.Integrated transportation systems, crew scheduling, metaheuristics
Using harmony search for optimising university shuttle bus driver scheduling for better operational management
Managing human resource to achieve specific goal in an organisation is a crucial task. One of various aspects in managing human resource is preparing optimum scheduling to perform certain tasks. The main objective of this paper is to illustrate the preparation and the work of optimum scheduling for university shuttle bus driver using a recently develop meta-heuristic technique known as Harmony Search. A mathematical formulation for the university shuttle bus driver scheduling problem based on the requirement and the preference of the university is illustrated. The optimum schedule is generated using Harmony Search, an optimisation approach inspired by the processes in music improvisation with less mathematical computation. It can be seen that the result produced using harmony search approach to automate the optimum university shuttle bus driver scheduling is quite promising because it yield better value of objective function compared with the one being done manually. Automation of the optimum university bus driver scheduling certainly can enhanced the operational management processes. This work can be regarded as a multidisciplinary work which several domains such as computer science, mathematics, operational research and management are involved
Optimization in driver’s scheduling for university shuttle bus using harmony search
This paper is about driver scheduling which is categorized as a difficult combinatorial problem. Driver scheduling is the process of assigning shift to the drivers based on hard and soft constraints. The proposed technique is Harmony Search, which is a recently developed population-based meta heuristic optimization algorithm. This study will be implemented to UTeM Shuttle Bus. The number of drivers involved is about 25. It is viewed that the objective function evaluated by Harmony Search is less than a manual solution. Therefore, the result produced for this project is quite promising since the objective function obtained is better than the real schedule which is done manually
A metaheuristic for crew scheduling in a pickup-and-delivery problem with time windows
A vehicle routing and crew scheduling problem (VRCSP) consists of
simultaneously planning the routes of a fleet of vehicles and scheduling the
crews, where the vehicle-crew correspondence is not fixed through time. This
allows a greater planning flexibility and a more efficient use of the fleet,
but in counterpart, a high synchronisation is demanded. In this work, we
present a VRCSP where pickup-and-delivery requests with time windows have to be
fulfilled over a given planning horizon by using trucks and drivers. Crews can
be composed of 1 or 2 drivers and any of them can be relieved in a given set of
locations. Moreover, they are allowed to travel among locations with
non-company shuttles, at an additional cost that is minimised. As our problem
considers distinct routes for trucks and drivers, we have an additional
flexibility not contemplated in other previous VRCSP given in the literature
where a crew is handled as an indivisible unit. We tackle this problem with a
two-stage sequential approach: a set of truck routes is computed in the first
stage and a set of driver routes consistent with the truck routes is obtained
in the second one. We design and evaluate the performance of a metaheuristic
based algorithm for the latter stage. Our algorithm is mainly a GRASP with a
perturbation procedure that allows reusing solutions already found in case the
search for new solutions becomes difficult. This procedure together with other
to repair infeasible solutions allow us to find high-quality solutions on
instances of 100 requests spread across 15 cities with a fleet of 12-32 trucks
(depending on the planning horizon) in less than an hour. We also conclude that
the possibility of carrying an additional driver leads to a decrease of the
cost of external shuttles by about 60% on average with respect to individual
crews and, in some cases, to remove this cost completely
Fairness aspects in personnel scheduling
In industries like health care, public transport or call centers a shift-based system
ensures permanent availability of employees for covering needed services. The resource
allocation problem – assigning employees to shifts – is known as personnel
scheduling in literature and often aims at minimizing staffing costs. Working in
shifts, though, impacts employees’ private lives which adds to the problem of increasing
staff shortage in recent years. Therefore, more and more effort is spent on
incorporating fairness into scheduling approaches in order to increase employees’
satisfaction. This paper presents a literature review of approaches for personnel
scheduling considering fairness aspects. Since fairness is not a quantitative objective,
but can be evaluated from different point of views, a large number of fairness
measurements exists in the literature. Furthermore, perspective (group vs individual
fairness) or time horizon (short-term vs long-term fairness) are often considered
very differently. To conclude, we show that a uniform definition and approach for
considering fairness in personnel scheduling is challenging and point out gaps for
future research
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