A heuristic procedure for one dimensional bin packing problem with additional constraints

We proposed a heuristic algorithm to solve the one-dimensional bin-packing problem with additional constraints. The proposed algorithm has been applied to solve a practical vehicle-allocation problem. The experimental results show that our proposed heuristic provides optimal or near-optimal results, and performs better than the first fit decreasing algorithm modified to incorporate additional constraints.

Factory Gate Pricing: An Analysis of the Dutch Retail Distribution

Factory Gate Pricing (FGP) is a relatively new phenomenon in retail distribution.Under FGP, products are no longer delivered at the retailer distribution center, but collected by the retailer at the factory gates of the suppliers.Owing to both the asymmetry in the distribution networks (the supplier sites greatly outnumber the retailer distribution centers) and the better inventory and transport coordination mechanisms, this is likely to result in high savings.A mathematical model was used to analyze the benefits of FGP for a case study in the Dutch retail sector.Extensive numerical results are presented to show the effect of the orchestration shift from supplier to retailer, the improved coordination mechanisms, and sector-wide cooperation.pricing;retailing;distribution;supply chain management;Netherlands

Factory Gate Pricing: An Analysis of the Dutch Retail Distribution

Factory Gate Pricing (FGP) is a relatively new phenomenon in retail distribution. Under FGP, products are no longer delivered at the retailer distribution center, but collected by the retailer at the factory gates of the suppliers. Owing to both the asymmetry in the distribution networks (the supplier sites greatly outnumber the retailer distribution centers) and the better inventory and transport coordination mechanisms, this is likely to result in high savings. A mathematical model was used to analyze the benefits of FGP for a case study in the Dutch retail sector. Extensive numerical results are presented to show the effect of the orchestration shift from supplier to retailer, the improved coordination mechanisms, and sector-wide cooperation.supply chain management;factory gate pricing;retail distribution

The integrated deterministic model for a vendor manage inventory in a two-stage supply chain

In a two-stage supply chain system, vendor managed inventory (VMI) policies is an integrating decisions between a supplier and his retailers.The supplier assumes the responsibility of maintaining inventory at its retailers and ensuring that they will not run out of stock at any moment.This paper discusses an optimization approach, considering the model of static demand on the inbound as well as the outbound inventory for a two-stage supply chain implementing VMI. In the proposed solutions for coordinating the single warehouse multiple-retailers (SWMR) system, retailers are first clustered to minimize the within-cluster travel costs and distances and are then replenished using an optimal direct shipping strategy satisfying some additional restriction

Lotsize optimization leading to a pp-median problem with cardinalities

We consider the problem of approximating the branch and size dependent demand of a fashion discounter with many branches by a distributing process being based on the branch delivery restricted to integral multiples of lots from a small set of available lot-types. We propose a formalized model which arises from a practical cooperation with an industry partner. Besides an integer linear programming formulation and a primal heuristic for this problem we also consider a more abstract version which we relate to several other classical optimization problems like the p-median problem, the facility location problem or the matching problem.Comment: 14 page

On the inventory routing problem with stationary stochastic demand rate

One of the most significant paradigm shifts of present business management is that individual businesses no longer participate as solely independent entities, but rather as supply chains (Lambert and Cooper, 2000). Therefore, the management of multiple relationships across the supply chain such as flow of materials, information, and finances is being referred to as supply chain management (SCM). SCM involves coordinating and integrating these multiple relationships within and among companies, so that it can improve the global performance of the supply chain. In this dissertation, we discuss the issue of integrating the two processes in the supply chain related, respectively, to inventory management and routing policies. The challenging problem of coordinating the inventory management and transportation planning decisions in the same time, is known as the inventory routing problem (IRP). The IRP is one of the challenging optimization problems in logis-tics and supply chain management. It aims at optimally integrating inventory control and vehicle routing operations in a supply network. In general, IRP arises as an underlying optimization problem in situations involving simultaneous optimization of inventory and distribution decisions. Its main goal is to determine an optimal distribution policy, consisting of a set of vehicle routes, delivery quantities and delivery times that minimizes the total inventory holding and transportation costs. This is a typical logistical optimization problem that arises in supply chains implementing a vendor managed inventory (VMI) policy. VMI is an agreement between a supplier and his regular retailers according to which retailers agree to the alternative that the supplier decides the timing and size of the deliveries. This agreement grants the supplier the full authority to manage inventories at his retailers'. This allows the supplier to act proactively and take responsibility for the inventory management of his regular retailers, instead of reacting to the orders placed by these retailers. In practice, implementing policies such as VMI has proven to considerably improve the overall performance of the supply network, see for example Lee and Seungjin (2008), Andersson et al. (2010) and Coelho et al. (2014). This dissertation focuses mainly on the single-warehouse, multiple-retailer (SWMR) system, in which a supplier serves a set of retailers from a single warehouse. In the first situation, we assume that all retailers face a deterministic, constant demand rate and in the second condition, we assume that all retailers consume the product at a stochastic stationary rate. The primary objective is to decide when and how many units to be delivered from the supplier to the warehouse and from the warehouse to retailers so as to minimize total transportation and inventory holding costs over the finite horizon without any shortages

Redesign of Three-Echelon Multi-Commodity Distribution Network

This research studies the distribution network redesign of an actual electronics company. The problems are formulated based on multi-echelon capacitated Location Routing Problem (LRP) with two commodities: home products and service items. The objective function consists of three components: facility cost, closing cost of facility and transportation cost. We propose solution method based on clustering technique. The problem is decomposed into the Facility Location Allocation Problem (FLAP) and the Multi-Depot Vehicle Routing Problem (MDVRP). MDVRP is solved by clustering method and feed the results to the modified FLAP to allocate the demand nodes to facilities and configure all distribution networks, for the 2nd and 3rd echelon. The distribution is divided into five region zones. Previously, each region was operated independently but this research compares the solutions from solving each region independently and solving all five zones simultaneously. The results indicate that the proposed solution method can achieve computation time and total cost that are comparable to ones obtained from solving the problem to optimality. Exact approach can only solve small and medium problems, whereas the proposed solution method provides the acceptable solution of real-life largest problem in limit of computation time. Finally, we perform sensitivity analysis on the results

Solution strategies for a supply chain deterministic model

To most firms, intelligent supply chain decisions are essential to achieve competitiveness in an environment characterized with increasing globalization and relentless changes. As the supply chain concept largely evolved from traditional logistics management, practitioners and researchers have historically focused on the individual processes of a supply chain. A wide array of mathematical models have been developed to tackle such functional issues as inventory level, lead-time performance, delivery performance, customer satisfaction and so on. This research presents a model that aims to evaluate and optimize the overall performance of the supply chain. The key nodes and variables in the model are composed of plant location and production volume, storage location and volume, transportation mode and volume. Optimization of the model is to minimize the total supply chain operation cost, expressed as the sum of production cost, storage cost, transportation cost and lost-sale cost. Our methodology is a three-phased approach. First, we build a mixed integer-programming model of 3-tier supply chain with multi-plant, multi-warehouse, and multi-retailer, multi-period and restricted capacity. This mathematical model is solved by CPLEX/OPL. Due to excessive computation time to reach the Optimal Solution, we introduce the second phase to develop heuristic solutions to reduce the computation time. In the final phase, we evaluate the proposed heuristic solutions. Result analysis shows that the computation time is generally exponentially correlated to the data size in seeking Optimal Solutions, whereas it generally follows the polynomial distribution when the Heuristic Solutions are applied. Consequently, Heuristic Solution is preferred for models with large size data

THE INVENTORY ROUTING PROBLEM WITH THIRD PARTY LOGISTICS

There are two key planning issues in supply chain: inventory management and transportation. In this research, the inventory control and transportation of syrup concentrate and final products for one bottling company working for a beverage company is studied. Operation of most of beverage companies is based on a franchised distribution system. In this operation, syrup concentrate is produced by a beverage company and sold to bottlers. Bottlers, in turn, mix the syrup concentrate with different ingredients to produce various products and distribute them to retailers. Unsatisfied orders have several harmful effects on the bottling company. The bottling company may not satisfy all demands due to its small fleet size, which is not able to cover all deliveries in the right timeframe. One method for preventing missed orders is sending orders to some retailers in advance to hold for future use. This allows the fleet to be free to service the rest of the retailers. This policy is possible if those retailers have available capacity to keep products. Another way to deal with this problem is by renting vehicles, which increases the fleet size. The last option for delivering to a retailer when the owned fleet is not able to do so is outsourcing shipping and/or warehousing. The bottling company contracts with a Third Party Logistics Provider (TPLP), who is responsible for delivery of final products to some of the bottler's retailers. Also, TPLPs can store commodities in their warehouses and deliver products to retailers at the right time if there is no available capacity in the bottler's warehouses. This problem belongs to Inventory Routing Problem (IRP) with some new features such as options for rental vehicle and TPLPs. IRP is a well-studied problem in Operation Research but most of the studies take a single period into account. In contrast, the proposed model in this study includes several time steps in which a decision in one time step can affect future time steps. The proposed model is a multi-tier, multi-plant, multi-warehouse, and multi-product model which considers non-homogeneous fleet. No model in the literature considers all of these characteristics simultaneously. In this research heuristic methods are developed to solve large problems for which optimization packages cannot find even a feasible solution. Two heuristic methods are proposed for this problem, which are based on fix-and-run algorithm. Three improvement phases are also developed to enhance the final solution of heuristics. The proposed heuristic methods in this research can find an appropriate feasible solution with only a small gap from an upper bound and in reasonable running time