Optimal Workers Allocation for the Crossdocking Just in Time Scheduling Problem

Hdl Handle:
http://hdl.handle.net/11285/572619
Title:
Optimal Workers Allocation for the Crossdocking Just in Time Scheduling Problem
Issue Date:
01/05/2007
Abstract:
In this work, a warehouse is allowed to function as a crossdock to minimize costs for a scheduling problem. These costs are due to two factors: the number of teams of workers hired to do the job, and the transit storage time for cargo. Each team of workers has a fixed cost per working day, and the cargo can incur early and tardy delivery costs. Then, the transit storage time for cargo is minimized according to Just in Time (JIT) scheduling. The goal is to obtain both: the optimal number of teams of workers in the crossdock and a schedule that minimizes the transit storage time for cargo. An integrated model to obtain both the optimal number of teams of workers and the schedule for the problem is written. The model uses the machine scheduling notation to describe it. Since the problem is known as NP-hard, a solution approach based on a combination of two metaheuristics, Reactive GRASP embedded in a Local Search algorithm and Tabu Search (RGLSTS), is provided. The results obtained from the exact method that uses the ILOG CPLEX 9.1 solver for 14 problem instances and the results obtained from the RGLSTS metaheuristic algorithm for the same problem instances are discussed. This research has an important academic contribution because it involves the development of a metaheuristic algorithm not previously applied to a relevant problem that has not received attention. Besides, the source codes of the programs that solve the problem are available for the reader and they can be modified according to the user needs. In the industry field, the algorithm mentioned above can be easily adapted in order to be applied to a real problem (i.e., large transshipments in companies like Wal-Mart, HEB, among others). Obtaining optimal or near optimal solutions for the problem of this work represents an improvement in the movement or distribution of the workforce and products, reducing this way, hiring costs, transportation costs and inventory costs.
Keywords:
Workers Allocation; Just In Time Scheduling; Machine Shceduling
Degree Program:
Program in Scinces of Engineering
Advisors:
José Luis González Velarde
Committee Member / Sinodal:
John Welsh Fowler
Degree Level:
Doctor of Philosophy in Engineering
School:
Escuela en Ingeniería y Arquitectura
Campus Program:
Campus Monterrey
Discipline:
Ingeniería y Ciencias Aplicadas / Engineering & Applied Sciences
Appears in Collections:
Ciencias Exactas

Full metadata record

DC FieldValue Language
dc.contributor.advisorJosé Luis González Velardees
dc.creatorÁlvarez Pérez, Guillermo A.en
dc.date.accessioned2015-08-17T11:36:42Zen
dc.date.available2015-08-17T11:36:42Zen
dc.date.issued01/05/2007-
dc.identifier.urihttp://hdl.handle.net/11285/572619en
dc.description.abstractIn this work, a warehouse is allowed to function as a crossdock to minimize costs for a scheduling problem. These costs are due to two factors: the number of teams of workers hired to do the job, and the transit storage time for cargo. Each team of workers has a fixed cost per working day, and the cargo can incur early and tardy delivery costs. Then, the transit storage time for cargo is minimized according to Just in Time (JIT) scheduling. The goal is to obtain both: the optimal number of teams of workers in the crossdock and a schedule that minimizes the transit storage time for cargo. An integrated model to obtain both the optimal number of teams of workers and the schedule for the problem is written. The model uses the machine scheduling notation to describe it. Since the problem is known as NP-hard, a solution approach based on a combination of two metaheuristics, Reactive GRASP embedded in a Local Search algorithm and Tabu Search (RGLSTS), is provided. The results obtained from the exact method that uses the ILOG CPLEX 9.1 solver for 14 problem instances and the results obtained from the RGLSTS metaheuristic algorithm for the same problem instances are discussed. This research has an important academic contribution because it involves the development of a metaheuristic algorithm not previously applied to a relevant problem that has not received attention. Besides, the source codes of the programs that solve the problem are available for the reader and they can be modified according to the user needs. In the industry field, the algorithm mentioned above can be easily adapted in order to be applied to a real problem (i.e., large transshipments in companies like Wal-Mart, HEB, among others). Obtaining optimal or near optimal solutions for the problem of this work represents an improvement in the movement or distribution of the workforce and products, reducing this way, hiring costs, transportation costs and inventory costs.en
dc.language.isoenen
dc.rightsOpen Accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleOptimal Workers Allocation for the Crossdocking Just in Time Scheduling Problemen
dc.typeTesis de Doctoradoes
thesis.degree.grantorInstituto Tecnológico y de Estudios Superiores de Monterreyes
thesis.degree.levelDoctor of Philosophy in Engineeringen
dc.contributor.committeememberJohn Welsh Fowleres
thesis.degree.disciplineEscuela en Ingeniería y Arquitecturaes
thesis.degree.nameProgram in Scinces of Engineeringen
dc.subject.keywordWorkers Allocationen
dc.subject.keywordJust In Time Schedulingen
dc.subject.keywordMachine Shcedulingen
thesis.degree.programCampus Monterreyes
dc.subject.disciplineIngeniería y Ciencias Aplicadas / Engineering & Applied Scienceses
All Items in REPOSITORIO DEL TECNOLOGICO DE MONTERREY are protected by copyright, with all rights reserved, unless otherwise indicated.