Modeling and solving the multi-period inventory routing problem with constant demand rates

The inventory routing problem (IRP) is one of the challenging optimization problems in supply chain logistics. It combines inventory control and vehicle routing optimization. The main purpose of the IRP is to determine optimal delivery times and quantities to be delivered to customers, as well as optimal vehicle routes to distribute these quantities. The IRP is an underlying logistical optimization problem for supply chains implementing vendor-managed inventory (VMI) policies, in which the supplier takes responsibility for the management of the customers' inventory. In this paper, we consider a multi-period inventory routing problem assuming constant demand rates (MP-CIRP). The proposed model is formulated as a linear mixed-integer program and solved with a Lagrangian relaxation method. The solution obtained by the Lagrangian relaxation method is then used to generate a close to optimal feasible solution of the MP-CIRP by solving a series of assignment problems. The numerical experiments carried out so far show that the proposed Lagrangian relaxation approach nds quite good solutions for the MP-CIRP and in reasonable computation times

The Downs-Thompson paradox in multimodal networks

Users of the transportation networks generally choose their routes in an independent and uncoordinated way in order to minimize their own perceived costs. This non-cooperative behaviour can lead to a suboptimal utilization of the network and, in some situations, increasing the network capacity can make the subutilization even worse. Such phenomenon is described in literature as traffic or network paradoxes. This paper provides a review on two famous network paradoxes, and also introduces a new one

Simulation based performance analysis of an end-of-Aisle automated storage and retrieval system

This paper presents and discusses simulation of an End-of-Aisle automated storage and retrieval system, using FLEXSIM 6. The objective of the simulation model is to analyze and compare results of different control policies and physical designs. The performance measures considered for the evaluation of each control policy and layout combination are the total travel time of the crane and the number of storage and retrieval operations performed. The experiments set up and the corresponding results are discussed

Using simulation to analyze picker blocking in manual order picking systems

The rise of the e-commerce practice makes the warehouses be confronted with ever smaller orders that must be met ever faster, often within a 24-h period. This pressures the order picking process as the orders pickers' workload becomes higher and higher, leading subsequently to congestion in the warehouse and impacting its productivity. It is therefore crucial to determine which order batching and picking policies enhance the performance of order picking activities. This paper carries out an intensive simulation study to examine the performance of different order picking policies with batching in a wide-aisle warehouse with a low-level picker-to-parts system. The performance of the system is measured in terms of total travelled distance, number of collisions between operators (congestion) and order lead times. A full factorial design is set up and the simulation output is statistically analyzed. The results are reported and thoroughly discussed

Optimizing operations of large-scale water supply networks: a case study

In this paper we propose a mathematical programming model for a large drinking water supply network and discuss some possible extensions. The proposed optimization model is of a real water distribution network, the largest water supply network in Flanders. The problem is nonlinear, nonconvex and involves some binary variables, making it belong to the class of NP-hard problems. We discuss a way to convexify the nonconvex term and show some results on two case instances of the actual network

Optimizing operations of large water supply networks: a case study

In this paper we propose a mathematical programming model for a large drinking water supply network and discuss some possible extensions. The proposed optimization model is of a real water distribution network, the largest water supply network in Flanders. The problem is nonlinear, nonconvex and involves some binary variables, making it belong to the class of NP-hard problems. We discuss a way to convexify the nonconvex term and show some results on two case instances of the actual network

Class-based storage location assignment : an overview of the literature

Storage, per se, is not only an important process in a warehouse, also it has the greatest influence on the most expensive one, i.e., order picking. This study aims to give a literature overview on class-based storage location assignment (CBSLAP). In this paper, we discuss storage policies and present a classification of storage location assignment problem. Next, different configuration of classes are presented. We identify the research gaps in the literature and conclude with promising future research directions

Aggregate constrained inventory systems with independent multi-product demand: control practices and theoretical limitations

In practice, inventory managers are often confronted with a need to consider one or more aggregate constraints. These aggregate constraints result from available workspace, workforce, maximum investment or target service level. We consider independent multi-item inventory problems with aggregate constraints and one of the following characteristics: deterministic leadtime demand, newsvendor, basestock policy, rQ policy and sS policy. We analyze some recent relevant references and investigate the considered versions of the problem, the proposed model formulations and the algorithmic approaches. Finally we highlight the limitations from a practical viewpoint for these models and point out some possible direction for future improvements