A GRASP-Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large-Scale Instances

Weaddressalogisticsdistrictingproblemfacedbyaparcelcompanywhoseoperationsconsistofpickingupanddeliveringpackages overaserviceregion.Thedistrictingprocessaimstofindapartitionoftheserviceregionintodeliveryandcollectionzonesthat may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large-scale instances. Numerical experimentation is performed consideringdifferentinstancesizesandtypes.Resultsshowthattheproposedsolutionapproachisabletosolvelarge-scaleinstances inreasonablecomputationaltimeswithgoodqualityofthesolutionsobtained.Todeterminethequalityofthesolutions,resultsare comparedwithCPLEXsolutionsandwiththecurrentrealsolutiontohighlightthebenefitsoftheproposedapproach.Conclusions andrecommendationsforfurtherresearchareprovided

A GRASP-Tabu Heuristic Approach to Territory Design for Pickup and Delivery Operations for Large-Scale Instances

We address a logistics districting problem faced by a parcel company whose operations consist of picking up and delivering packages over a service region. The districting process aims to find a partition of the service region into delivery and collection zones that may be served by a single vehicle that departs from a central depot. Criteria to be optimized are to balance workload content among the districts and to create districts of compact shape. A solution approach based on a hybrid procedure that combines elements of GRASP and Tabu Search (TS) is proposed to solve large-scale instances. Numerical experimentation is performed considering different instance sizes and types. Results show that the proposed solution approach is able to solve large-scale instances in reasonable computational times with good quality of the solutions obtained. To determine the quality of the solutions, results are compared with CPLEX solutions and with the current real solution to highlight the benefits of the proposed approach. Conclusions and recommendations for further research are provided

Modeling and Analysis of Manufacturing Systems

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Design and Analysis of Lean Production System

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Project selection, scheduling and resource allocation with time dependent returns

In this paper we formulate and analyze the joint problem of project selection and task scheduling. We study the situation where a manager has many alternative projects to pursue such as developing new product platforms or technologies, incremental product upgrades, or continuing education of human resources. Project return is assumed to be a known function of project completion time. Resources are limited and renewable. The objective is to maximize present worth of profit. A general mathematical formulation that can address several versions of the problem is presented. An implicit enumeration procedure is then developed and tested to provide good solutions based on project ordering and a prioritization rule for resource allocation. The algorithm uses an imbedded module for solving the resource-constrained project scheduling problem at each stage. The importance of integrating the impact of resource constraints into the selection of projects is demonstrated.Project management Project selection Integer programming Heuristics Implicit enumeration