Exact methods and a heuristic for the optimization of an integrated replenishment‐storage planning problem (original) (raw)

A dynamic replenishment system for integrating supply chain warehousing and transportation functions

2004

An integrated supply chain (SC) model comprising both the warehousing and the transportation functions of the SC is developed that can help to reduce SC inventory levels and total SC costs while maintaining and/or improving customer service levels under dynamic operating conditions. The dynamic replenishment system (DRS) is first defined in the context of a mixed integer programming (MIP) model ('the DRS MIP model'). However, due to the unacceptably long computation times associated with the MIP formulation, a new heuristic algorithm ('the DRS heuristic') is developed to find good, potentially near-optimal solutions to the same static SC problem instances. The performance of the DRS heuristic is subsequently evaluated under dynamic SC conditions with the aid of discrete event simulation. The DRS heuristic is embedded into the ProModel simulation model as a callable subroutine that can be used to make replenishment and transportation decisions throughout the SC ('the DRS simulation model'). Experimental results confirm that operating a SC under DRS simulation model constructs is a win-win relationship for SC partners. The DRS has proven to be able to meet its primary goal of reacting effectively and efficiently to normal and/or nonnormal (unplanned, disruptive) SC operations.

A Dynamic Replenishment System for Integrating Supply Chain functions

Maritime Economics & Logistics, 2007

Mixed Integer Linear Programming for delivery planning in Joint Replenishment Problems

2013 International Conference on Control, Decision and Information Technologies (CoDIT), 2013

This paper deals with the Joint Replenishment Problem (JRP) in multi item and multi site settings based on the common cycle strategy. The proposed delivery planning method, in deterministic and constant demand environment, uses Mixed Integer Linear Programming (MILP) algorithm. It is shown that the proposed MILP method gives better results in terms of reduced total replenishment cost than the standard delivery policy for which there is a periodicity of delivery for all the pairs (product, site).

Optimal Solutions for a Multi-Product, Multi-Echelon Production and Replenishment System

International Journal of Information Systems and Supply Chain Management, 2009

The effective coordination is a key element in the success of many cooperative supply chains. All production, distribution and supply must be adequately synchronized in order to satisfy the customer needs and at the same time optimizing the operational costs. This article presents a multi-product, multi-echelon inventory system which comprises one manufacturer, a number of distribution centers and a number of retailers which are dependent of such distribution centers. The coordination and collaboration is achieved through a carefully designed replenishment policy. The near-optimal order quantities for each of the supply chain agents are calculated with a mathematical model in which the integrality constraints are relaxed. A number of instances were generated and tested. The results show the validity of the proposed approach.

A Constructive Heuristic for the Integrated Inventory-Distribution Problem

2008

We study the integrated inventory distribution problem which is concerned with multiperiod inventory holding, backlogging, and vehicle routing decisions for a set of customers who receive units of a single item from a depot with infinite supply. We consider an environment in which the demand at each customer is deterministic and relatively small compared to the vehicle capacity, and the customers are located closely such that a consolidated shipping strategy is appropriate. We develop a constructive heuristic to obtain an approximate solution for this NP-hard problem and demonstrate its effectiveness through computational experiments.

AN INNOVATIVE HEURISTIC FOR JOINT REPLENISHMENT PROBLEM WITH DETERMINISTIC AND STOCHASTIC DEMAND

International Journal of …, 2010

Joint replenishment problem (JRP) is a common real problem which aims to minimize order cost and inventory holding cost. In this paper, classical, centralized and decentralized JRP models are discussed. An innovative heuristic to minimize the total cost is implemented for each model. This heuristic seeks to balance the order cost and the inventory holding costs. The results show that the innovative heuristic can best be implemented in the classical and decentralized models. For stochastic demand such as Poisson or Exponential distribution, the innovative heuristic can be implemented with the random variables which are generated by Monte Carlo simulation. and decentralized models; 2) to develop innovative heuristic procedure for models with deterministic and stochastic demand. We show how the innovative heuristic approach can minimize the total cost.

Multi-product joint delivery planning in a retailers’ network under resource constraints

International Journal of Systems Science: Operations & Logistics, 2015

The main objective of the JRP (Joint Replenishment Problem) is to build a delivery program so as to satisfy local demands while minimizing the total cost including ordering and storage costs. The classical nonlinear formulation of this problem can be seen as a multi-product and multi-site extension of the Economic Order Quantity (EOQ) problem. If demand rates are fixed and known, the problem allows a periodic solution, in which an optimal delivery program repeats indefinitely. In the unconstrained case, the delivery plan has two levels of periodicity: a global periodicity for the delivery sequence and a particular periodicity for each product and site. The main purpose of this paper is to combine in the same model grouping, transportation, and storage issues. Constraints on transportation capacity and routing are introduced in a linear reformulation of the problem, leading to a better coordination of delivery schedules with respect to products and sites. The superiority of the proposed method is that it provides the optimal route of delivery for each tour and permits minimization of the maximal delivery capacity, whereas other existing methods could not offer such important features.

The Storage Replenishment Problem in Rectangular Warehouses

2016

In warehouses, storage replenishment operations involve the transportation of items to capacitated item slots in forward storage area from reserve storage. These items are later picked from these slots as their demand arises. While order picking constitutes the majority of warehouse operating costs, replenishment operations might be as costly in warehouses where pick lists generally consist of only a few lines (e.g., order fulfillment warehouses). In this study, we consider the storage replenishment problem in a parallel-aisle warehouse, where replenishment and order picking operations are carried out in successive waves with time limits. The aim is to determine the item slots that will be replenished and the route of the replenishment worker in each replenishment wave, so as to minimize the total labor and travel costs, and ensure the availability of items at the start of the wave they will be picked. The problem is analogous to the inventory routing problem due to the inherent tra...

An efficient algorithm for a generalized joint replenishment problem

European Journal of Operational Research, 1999

In most multi-item inventory systems, the ordering costs consist of a major cost and a minor cost for each item included. Applying for every individual item a cyclic inventory policy, where the cycle length is a multiple of some basic cycle time, reduces the major ordering costs. An ecient algorithm to determine the optimal policy of this type is discussed in this paper. It is shown that this algorithm can be used for deterministic multi-item inventory problems, with general cost rate functions and possibly service level constraints, of which the well-known joint replenishment problem is a special case. Some useful results in determining the optimal control parameters are derived, and worked out for piecewise linear cost rate functions. Numerical results for this case show that the algorithm signicantly outperforms other solution methods, both in the quality of the solution as in the running time.

Exact methods and a heuristic for the optimization of an integrated replenishment‐storage planning problem (original) (raw)

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