Problem Reduction in Set Partitioning Problems

In this paper, several problem reduction techniques are discussed that can be used to reduce the solution time of set partitioning problems. These techniques can be applied in any solution algorithm for set partitioning problems. Besides a short review of the existing literature on preprocessing set partitioning problems, we also present several new techniques. The value of these techniques is illustrated by various computational experiments.algorithm;problem reducing

A Lagrangean Relaxtion Based Algorithm for Solving Set Partitioning Problems

In this paper we discuss a solver that is developed to solve set partitioning problems.The methods used include problem reduction techniques, lagrangean relaxation and primal and dual heuristics.The optimal solution is found using a branch and bound approach.In this paper we discuss these techniques.Furthermore, we present the results of several computational experiments and compare the performance of our solver with the well-known mathematical optimization solver Cplex.algorithm;integer programming

Advanced Planning Concepts in the Closed-Loop Container Network of ARN

In this paper we discuss a real-life case study in the optimization of the logistics network for the collection of containers from end-of-life vehicle dismantlers in the Netherlands.Advanced planning concepts like dynamic assignment of dismantlers to logistic service providers are analyzed by a simulation model.In this model, we periodically solve a vehicle routing problem to gain insight in the long-term performance of the system.The vehicle routing problem considered is a multi depot pickup and delivery problem with alternative delivery locations.We solve this problem with a heuristic based on route generation and set partitioning.Reverse logistics;Closed-loop supply chain mmanagement;vehicle routing;set partitioning;distribution planning

A Lagrangean Relaxtion Based Algorithm for Solving Set Partitioning Problems

In this paper we discuss a solver that is developed to solve set partitioning problems.The methods used include problem reduction techniques, lagrangean relaxation and primal and dual heuristics.The optimal solution is found using a branch and bound approach.In this paper we discuss these techniques.Furthermore, we present the results of several computational experiments and compare the performance of our solver with the well-known mathematical optimization solver Cplex.

Collector Managed Inventory, A Proactive Planning Approach to the Collection of Liquids coming from End-of-life Vehicles

In this article we introduce Collector Managed Inventory (CMI) as the reverse logistics counter part of Vendor Managed Inventory (VMI).The collection company takes responsibility for the inventories of cores or materials to be recycled.Experience in forward supply chain management has shown the potential of VMI by bringing the coordination of transportation and inventory decisions to the same supply chain entity.Using information technology called telemetry, we are able to monitor inventory levels at distance.We introduce a proactive planning methodology based on two types of collection orders: must- and can-orders.Every collection period all must-orders have to be collected, while canorders are only collected if they can be combined beneficially with the must-orders.The routing problem is solved by a combination of route generation and set partitioning.The system is illustrated in a real-life case study for Auto Recycling Nederland on the collection of liquids coming from end-oflife vehicles, such as coolant and oil.In several scenarios the old reactive approach is compared to the proactive approach resulting in cost savings up to about 19%.supply;logistics;vehicle routine;distribution;information technology;inventory

Collector Managed Inventory, A Proactive Planning Approach to the Collection of Liquids coming from End-of-life Vehicles

In this article we introduce Collector Managed Inventory (CMI) as the reverse logistics counter part of Vendor Managed Inventory (VMI).The collection company takes responsibility for the inventories of cores or materials to be recycled.Experience in forward supply chain management has shown the potential of VMI by bringing the coordination of transportation and inventory decisions to the same supply chain entity.Using information technology called telemetry, we are able to monitor inventory levels at distance.We introduce a proactive planning methodology based on two types of collection orders: must- and can-orders.Every collection period all must-orders have to be collected, while canorders are only collected if they can be combined beneficially with the must-orders.The routing problem is solved by a combination of route generation and set partitioning.The system is illustrated in a real-life case study for Auto Recycling Nederland on the collection of liquids coming from end-oflife vehicles, such as coolant and oil.In several scenarios the old reactive approach is compared to the proactive approach resulting in cost savings up to about 19%.

Solving set partitioning problems using lagrangian relaxation

This thesis focuses on the set partitioning problem. Given a collection of subsets of a certain root set and costs associated to these subsets, the set partitioning problem is the problem of finding a minimum cost partition of the root set. Many real-life problems, such as vehicle routing and crew scheduling problems, can be formulated as set partitioning problems. The LaRSS solver is developed for solving set partitioning problems fast without using external linear programming solvers. The methods used include Lagrangian relaxation, preprocessing techniques and branch and bound. This thesis describes many research results coming from the development of LaRSS. Moreover, the performance of LaRSS is discussed and compared with the well-known optimization package CPLEX. Finally, two cases in the field of vehicle routing are described to illustrate the use of LaRSS in real-life situations

Problem Reduction in Set Partitioning Problems

In this paper, several problem reduction techniques are discussed that can be used to reduce the solution time of set partitioning problems. These techniques can be applied in any solution algorithm for set partitioning problems. Besides a short review of the existing literature on preprocessing set partitioning problems, we also present several new techniques. The value of these techniques is illustrated by various computational experiments.

Problem Reduction in Set Partitioning Problems

In this paper, several problem reduction techniques are discussed that can be used to reduce the solution time of set partitioning problems. These techniques can be applied in any solution algorithm for set partitioning problems. Besides a short review of the existing literature on preprocessing set partitioning problems, we also present several new techniques. The value of these techniques is illustrated by various computational experiments

Advanced Planning Concepts in the Closed-Loop Container Network of ARN

In this paper we discuss a real-life case study in the optimization of the logistics network for the collection of containers from end-of-life vehicle dismantlers in the Netherlands.Advanced planning concepts like dynamic assignment of dismantlers to logistic service providers are analyzed by a simulation model.In this model, we periodically solve a vehicle routing problem to gain insight in the long-term performance of the system.The vehicle routing problem considered is a multi depot pickup and delivery problem with alternative delivery locations.We solve this problem with a heuristic based on route generation and set partitioning