4 Presentations

• 
  11:00 AM - 11:25 AM

  Multi-Period Collection of Recyclable Materials

  • Maria Elbek, presenter, Aarhus University
  • Sanne Wøhlk, Aarhus University

  We consider an approach for scheduling the multi-period collection of recyclable materials. To establish a high service level for the citizens, cubes for collection may not be overfilled. Inspired by theory on the IRP, we present a deterministic solution method for scheduling the collection in order to minimize the operation cost.

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  11:25 AM - 11:50 AM

  A Stochastic Solution Approach for Multi-Period Collection of Recyclable Materials

  • Maria Elbek, presenter, Aarhus University
  • Teodor Crainic, Université de Montréal
  • Walter Rei, Université de Montréal

  We consider an approach for scheduling the multi-period collection of recyclable materials. To establish a high service level for the citizens, cubes for collection may not be overfilled. Inspired by theory on the IRP, we present a two-stage stochastic model and solution method for scheduling the collection in order to minimize the cost.

• 
  11:50 AM - 12:15 PM

  A Tabu Search for the Multi-zone Multi-trip Pickup and Delivery Problem with Time Window and Synchronization

  • Phuong Nguyen Khanh, presenter, Université de Montréal
  • Teodor Gabriel Crainic, Université du Québec à Montréal
  • Michel Toulouse, Oklahoma State University

  The Multi-zone Multi-trip Pickup and Delivery Problem with Time Window and Synchronization has two sets of intertwined decisions: the routing decisions which determine the sequence of customers visited by each vehicle route, the scheduling decisions which plan movements of vehicles between facilities within time synchronization restrictions. We propose a tabu search algorithm integrating multiple neighborhoods targeted to the decision sets of the problem. To assess the proposed algorithm, test have been conducted on the first benchmark instances of the problem which have up to 72 facilities and 7200 customer demands.

• 
  12:15 PM - 12:40 PM

  An Adaptive Large-Neighborhood Search Heuristic for a Multi-Period Vehicle Routing Problem

  • Iman Dayarian, presenter, Université de Montréal
  • Teodor Gabriel Crainic, Université du Québec à Montréal
  • Michel Gendreau, Polytechnique Montréal
  • Walter Rei, Université du Québec à Montréal

  We consider tactical planning for a particular class of multi-period vehicle routing problems (MPVRP). This problem involves optimizing product collection and distribution from several production locations to a set of processing plants over a planning horizon. Each horizon consists of several days, and the collection-distribution are performed on a repeating daily basis. In this context, a single routing plan must be prepared for the whole horizon, taking into account the seasonal variations in the supply. We model the problem using a sequence of periods, each corresponding to a season, and intra-season variations are neglected. We propose an adaptive large-neighborhood search with several special operators and features. To evaluate the performance of the algorithm we performed an extensive series of numerical tests. The results show the excellent performance of the algorithm in terms of solution quality and computational efficiency.