Zeger Degraeve

An evaluation of vendor selection models from a total cost of ownership perspective

Abstract Many different vendor selection models have been published in the purchasing literature. However there has been no systematic approach to compare the relative efficiency of the systems. In this paper we propose to use the concept of Total Cost of Ownership as a basis for comparing vendor selection models. We illustrate the comparison with a real life data set of the purchasing problem of ball bearings at Cockerill Sambre, a Belgian multinational company in the steel industry. From a Total Cost of Ownership perspective mathematical programming models outperform rating models and multiple item models generate better results than single item models for this specific case study.

Meta-heuristics for dynamic lot sizing: A review and comparison of solution approaches

Proofs from complexity theory as well as computational experiments indicate that most lot sizing problems are hard to solve. Because these problems are so difficult, various solution techniques have been proposed to solve them. In the past decade, meta-heuristics such as tabu search, genetic algorithms and simulated annealing, have become popular and efficient tools for solving hard combinational optimization problems. We review the various meta-heuristics that have been specifically developed to solve lot sizing problems, discussing their main components such as representation, evaluation neighborhood definition and genetic operators. Further, we briefly review other solution approaches, such as dynamic programming, cutting planes, Dantzig-Wolfe decomposition, Lagrange relaxation and dedicated heuristics. This allows us to compare these techniques. Understanding their respective advantages and disadvantages gives insight into how we can integrate elements from several solution approaches into more powerful hybrid algorithms. Finally, we discuss general guidelines for computational experiments and illustrate these with several examples.

Modeling Industrial Lot Sizing Problems: A Review

In this paper we give an overview of recent developments in the field of modeling deterministic single-level dynamic lot sizing problems. The focus of this paper is on the modeling of various industrial extensions and not on the solution approaches. The timeliness of such a review stems from the growing industry need to solve more realistic and comprehensive production planning problems. First, several different basic lot sizing problems are defined. Many extensions of these problems have been proposed and the research basically expands in two opposite directions. The first line of research focuses on modeling the operational aspects in more detail. The discussion is organized around five aspects: the set ups, the characteristics of the production process, the inventory, demand side and rolling horizon. The second direction is towards more tactical and strategic models in which the lot sizing problem is a core substructure, such as integrated production–distribution planning or supplier selection. Recent advances in both directions are discussed. Finally, we give some concluding remarks and point out interesting areas for future research.

Improving the efficiency of the purchasing process using total cost of ownership information: The case of heating electrodes at Cockerill Sambre S.A.

Improving the efficiency of the purchasing process provides important opportunities to increase a firms profitability. In this paper we introduce a mathematical programming model that uses total cost of ownership information to simultaneously select suppliers and determine order quantities over a multi-period time horizon. The total cost of ownership quantifies all costs associated with the purchasing process and is based on the activities and cost drivers determined by an activity based costing system. Our approach is motivated by the purchasing problem of heating electrodes at Cockerill Sambre, a Belgian multinational steel producer. In this case quality issues account for more than 70% of the total cost of ownership making the quality of a supplier a critical success factor in the supplier selection process.

A Mathematical Programming Approach for Procurement Using Activity Based Costing

Activity Based Costing and Management are important topics in todays management accounting literature. While there has been much attention paid in the Activity Based Costing literature to customer profitability analysis, process improvement and product design, there has been far less notice taken of purchasing. In this paper we develop an Activity Based Costing approach for the determination of procurement strategies. Vendor selection using an Activity Based Costing approach is choosing the combination of suppliers for a given product group that minimizes the total costs associated with the purchasing strategy. To this end we develop a mathematical programming model where decisions involve the selection of vendors and the determination of order quantities. The system computes the total cost of ownership, thereby increasing the objectivity in the selection process and giving the opportunity for various kinds of sensitivity analysis. Copyright Blackwell Publishers Ltd 2000.

Broadcast Scheduling for Mobile Advertising

We describe a broadcast scheduling system developed for a precision marketing firm specialized in location-sensitive permission-based mobile advertising using SMS (Short Message Service) text messaging. Text messages containing advertisements were sent to registered customers when they were shopping in one of two shopping centers in the vicinity of London. The ads typically contained a limited-time promotional offer. The companys problem was deciding which ads to send out to which customers at what particular time, given a limited capacity of broadcast time slots, while maximizing customer response and revenues from retailers paying for each ad broadcast. We solved the problem using integer programming with an interface in Microsoft Excel. The system significantly reduced the time required to schedule the broadcasts, and resulted both in increased customer response and revenues.

The use of Total Cost of Ownership for strategic procurement: a company-wide management information system

We present a general company-wide management information system for defining procurement strategies. We believe that existing practices for determining purchasing strategies can be improved and a new approach developed. The system uses total cost of ownership information. We argue that mathematical programming models should be used for exploiting this information, when evaluating the firms strategic procurement options. As an example, we show how we have successfully applied our approach to develop a decision support system at Usinor, a European multinational steel company.

A New Dantzig-Wolfe Reformulation and Branch-and-Price Algorithm for the Capacitated Lot-Sizing Problem with Setup Times

Although the textbook Dantzig-Wolfe decomposition reformulation for the capacitated lot-sizing problem, as already proposed by Manne [Manne, A. S. 1958. Programming of economic lot sizes. Management Sci.4(2) 115--135], provides a strong lower bound, it also has an important structural deficiency. Imposing integrality constraints on the columns in the master program will not necessarily give the optimal integer programming solution. Mannes model contains only production plans that satisfy the Wagner-Whitin property, and it is well known that the optimal solution to a capacitated lot-sizing problem will not necessarily satisfy this property. The first contribution of this paper answers the following question, unsolved for almost 50 years: If Mannes formulation is not equivalent to the original problem, what is then a correct reformulation? We develop an equivalent mixed-integer programming (MIP) formulation to the original problem and show how this results from applying the Dantzig-Wolfe decomposition to the original MIP formulation. The set of extreme points of the lot-size polytope that are needed for this MIP Dantzig-Wolfe reformulation is much larger than the set of dominant plans used by Manne. We further show how the integrality restrictions on the original setup variables translate into integrality restrictions on the new master variables by separating the setup and production decisions. Our new formulation gives the same lower bound as Mannes reformulation. Second, we develop a branch-and-price algorithm for the problem. Computational experiments are presented on data sets available from the literature. Column generation is accelerated by a combination of simplex and subgradient optimization for finding the dual prices. The results show that branch-and-price is computationally tractable and competitive with other state-of-the-art approaches found in the literature.

Total cost of ownership purchasing of a service: The case of airline selection at Alcatel Bell

Abstract The multiple objective problem of purchasing for business falls into two broad categories: the purchasing of components for manufacturing and the purchasing of services. Several supplier selection models have been suggested in the literature for the purchasing of production-related components. To our knowledge, no supplier selection model for the purchasing of services has been published. In this paper we elaborate on a mathematical programming model that selects suppliers of a multiple item service and simultaneously determines market shares of the suppliers selected. The methodology is based on the collection of total cost of ownership (TCO) information, quantifying all the costs associated with the purchasing process throughout the entire value chain of the firm. We apply this methodology to the real life case study of selecting airlines for 56 destinations at Alcatel Bell and have obtained TCO savings of 19.5%.

Constructing a Total Cost of Ownership supplier selection methodology based on Activity-Based Costing and mathematical programming

Abstract In this paper we elaborate on a Total Cost of Ownership (TCO) supplier selection methodology that we have constructed using real life case studies of three different industrial components groups in a firm. These case studies are presented in this article. Analysing the value chain of the firm, data on the costs generated by the purchasing policy and on supplier performance are collected using Activity-Based Costing (ABC). Since a spreadsheet cannot encompass all these costs, let alone optimise the supplier selection and inventory management policy, a mathematical programming model is used. For a specific component group the combination of suppliers is selected that minimises the TCO. TCO takes into account all costs that the purchase and the subsequent use of a component entail in the entire value chain of the company. The TCO approach goes beyond minimising purchase price and studies all costs that occur during the entire life cycle of the item in the organisation. Possible savings of between 6% and 14% of the total cost of ownership of the current purchasing policy are obtained for the three cases. ABC is not an optimisation tool as such, but provides important accurate input to the optimising mathematical program, whereas the Operations Research literature usually only distinguishes between variable and fixed costs. We show that the integration of both delivers better results in the setting we have studied.