A mathematical programming approach for supplier selection using Activity Based Costing.

Vendor selection is an important problem in today's competitive environment . Decisions involve the selection of vendors and the determination of order quantities to be placed with the selected vendors. In this research we develop a mathematical programming model for this purpose using an Activity Based Costing approach. The system computes the total cost of ownership, thereby increasing the objectivity in the selection process and giving the opportunity for different kinds of sensitivity analysis. Moreover, it allow the analyst to objectively evaluate alternative purchasing policies due to the underlying analytic and rigorous decision model.Activity based costing; Mathematical programming; Selection;

Determining sourcing strategies : A decision model based on activity and cost driver information.

Determing sourcing strategies for different material groups provides a major challenge to most companies. There has been little research on the choice of the optimal number of different suppliers for a given product group and the determination of their market shares. In this paper we propose a mathematical programming model using activity based costing information to determine optimal order splitting among suppliers on the basis of the different costs associated with the purchasing decision. We argue that sourcing strategies should be based on the minimisation of the total cost of ownership resulting from external purchases. The model is applied to the case of ball bearings at Cockerill Sambre S.A., a Belgian multinational company in the steel industry.Model; Sourcing; Strategy;

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 firm's 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 S.A. 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 vendor selection process.Efficiency; Heating; Processes; Purchasing;

A polyhedral approach for the generalized assignment problem.

The generalized assignment problem (GAP) consists of finding a maximal profit assignment of n jobs over m capacity constrained agents, whereby each job has to be processed by only one agent. This contribution approaches the GAP from the polyhedral point of view. A good upper bound is obtained by approximating the convex hull of the knapsack constraints in the GAP-polytope using theoretical work of Balas. Based on this result, we propose a procedure for finding close-to-optimal solutions, which gives us a lower bound. Computational results on a set of 60representative and highly capacitated problems indicate that these solutions lie within 0.06% of the optimum. After applying some preprocessing techniques and using the obtained bounds, we solve the generated instances to optimality by branch and bound within reasonable computing time.Assignment;

Applying total cost of ownership for strategic procurement : three industrial case studies.

In this paper we elaborate on a Total Cost of Ownership supplier selection methodology that we have constructed using three real life case studies which 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. Possible savings of between 6 and 14% are obtained for the three cases.Case studies; Studies;

An evaluation of vendor selection models from a Total Cost of Ownership perspective.

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 real life data set of the purchasing problem of ball bearings at Cockerill Sambre, a Belgian multinational company in the steel industry. Mathematical programming models outperform rating models and multiple item models generate better results than single item models from a Total Cost of Ownership perspective for this specific case study.Evaluation; Models; Selection;

Total cost of ownership purchasing of a service : the case of airline slection at Alcatel Bell.

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%.Purchasing; Selection; Manufacturing; Models; Mathematical programming; Suppliers;

Modeling Industrial Lot Sizing Problems: A Review

In this paper we give an overview of recent developments in the field of modeling single-level dynamic lot sizing problems. The focus of this paper is on the modeling 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

A New Dantzig-Wolfe Reformulation And Branch-And-Price Algorithm For The Capacitated Lot Sizing Problem With Set Up Times

The textbook Dantzig-Wolfe decomposition for the Capacitated Lot Sizing Problem (CLSP),as already proposed by Manne in 1958, has an important structural deficiency. Imposingintegrality constraints on the variables in the full blown master will not necessarily give theoptimal IP solution as only production plans which satisfy the Wagner-Whitin condition canbe selected. It is well known that the optimal solution to a capacitated lot sizing problem willnot necessarily have this Wagner-Whitin property. The columns of the traditionaldecomposition model include both the integer set up and continuous production quantitydecisions. Choosing a specific set up schedule implies also taking the associated Wagner-Whitin production quantities. We propose the correct Dantzig-Wolfe decompositionreformulation separating the set up and production decisions. This formulation gives the samelower bound as Manne's reformulation and allows for branch-and-price. We use theCapacitated Lot Sizing Problem with Set Up Times to illustrate our approach. Computationalexperiments are presented on data sets available from the literature. Column generation isspeeded up by a combination of simplex and subgradient optimization for finding the dualprices. The results show that branch-and-price is computationally tractable and competitivewith other approaches. Finally, we briefly discuss how this new Dantzig-Wolfe reformulationcan be generalized to other mixed integer programming problems, whereas in the literature,branch-and-price algorithms are almost exclusively developed for pure integer programmingproblems