Total Value Of Purchasing Research Articles

An integrated grey-based multi-criteria optimisation approach for sustainable supplier selection and procurement-distribution planning

Increasing pressure from government and stakeholders has led manufacturing companies to initiate sustainable practices into their supply chains (SCs). Integrating practices like sustainable supplier selection, performance-based order allocation and carbon efficient distribution planning can immensely improve companies' sustainable image and hence provide a competitive edge. The current study focuses on the development of an integrated two-stage multi-attribute optimisation model to discuss these issues. In first stage, Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique based on grey numbers along with grey relational analysis (GRA) is utilised to evaluate suppliers' performance based on influential attributes. In the second stage, a multi-objective optimisation model was developed to optimise system's total cost, carbon emission and total value of purchasing (TVP) while contemplating delivery time windows. Weighted goal programming approach is utilised further for obtaining trade-off among multiple objectives. To validate the effectiveness of proposed methodology, a case study of an electronics company is considered.

An integrated grey-based multi-criteria optimisation approach for sustainable supplier selection and procurement-distribution planning

Increasing pressure from government and stakeholders has led manufacturing companies to initiate sustainable practices into their supply chains (SCs). Integrating practices like sustainable supplier selection, performance-based order allocation and carbon efficient distribution planning can immensely improve companies' sustainable image and hence provide a competitive edge. The current study focuses on the development of an integrated two-stage multi-attribute optimisation model to discuss these issues. In first stage, Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique based on grey numbers along with grey relational analysis (GRA) is utilised to evaluate suppliers' performance based on influential attributes. In the second stage, a multi-objective optimisation model was developed to optimise system's total cost, carbon emission and total value of purchasing (TVP) while contemplating delivery time windows. Weighted goal programming approach is utilised further for obtaining trade-off among multiple objectives. To validate the effectiveness of proposed methodology, a case study of an electronics company is considered.

Integrated analytic hierarchy process and mixed integer programming for supplier selection in mold and dies industry

PT. GMT has a mission to deliver the products to the customer on time and high-quality products to improve services. Sometimes, the delivery of product delays caused by the raw materials delays or didn't meet specifications. Selection optimal suppliers of raw materials are one of the solutions. There are two factors must be considered for the selection of suppliers, qualitative factors and quantitative factors. In this study, for qualitative factors, based on the criteria needed by PT GMT. This research produces three Linear Programming models, first: a qualitative objective function that will be maximized called the Total Value of Purchase (TVP). TVP is an integration of the Analytical Hierarchy Process (AHP) and Mix Integer Programming Integration. Second, the quantitative objective function for the procurement cost of raw materials, which is called the Total Cost of Purchase (TCP). The third is to optimize qualitative and quantitative simultaneously using the Goal Programming method. The selection of suppliers based on TVP the total value is 97.25, and the total procurement cost is Rp. 36,914,000, based on TCP, the total value is 89.14, and the total of procurement cost is IDR 31,356,000, while based on Goal Programming, the total value is 93.18, and the total of procurement cost is IDR 32,621,000. PT GMT has been able to determine the optimal supplier based on the policies set.

Multi-criteria optimization model integrated with AHP for evaluation and selection of COTS components

This paper deals with COTS evaluation and selection for developing a modular software system under single application development task. We consider both quantitative and qualitative criteria which fulfils the specific needs of a software system. We use analytical hierarchy process (AHP) technique for evaluating the fitness of COTS components based upon various criteria and sub-criteria thereby providing overall score of each COTS component. We develop optimization models integrating AHP and multi-criteria decision-making, which aim at: (i) maximize the total value of purchasing (TVP) subject to budget, compatibility and reliability constraints, and (ii) maximize TVP and minimize the total cost of purchase simultaneously subject to compatibility and reliability constraints. The efficiency of the models is illustrated by means of numerical illustrations.

Modeling synergies in multi-criteria supplier selection and order allocation: An application to commodity trading

We propose a novel meta-approach to support collaborative multi-objective supplier selection and order allocation (SSOA) decisions by integrating multi-criteria decision analysis and linear programming (LP). The proposed model accounts for suppliers’ performance synergy effects within a hierarchical decision structure. It incorporates both heterogeneous objective data and subjective judgments of the decision makers (DMs) representing various groups with different voting powers (VPs). We maximize the total value of purchasing (TVP) by optimizing order quantity assignment to suppliers and taking into consideration their synergies encountered in different time horizons. We apply the proposed model to a contractor selection and order quantity assignment problem in an agricultural commodity trading (ACT) company. We maximize the strategic effectiveness of both the customers and the suppliers, minimize risks, increase the degree of cooperation between trading partners on all levels of supply chain integration, enhance transparent knowledge sharing and aggregation, and support collaborative decision making.

An integration of a hybrid modified TOPSIS with a PGP model for the supplier selection with interdependent criteria

This paper deals with the supplier selection process when the criteria of selection are not independent. The primary aim is to illustrate that ignoring the interdependencies among these criteria leads to an unrealistic decision. Since supplier selection is a multiple-criteria decision-making (MCDM) process, the general structures of the relative methods are outlined in this paper. The proposed methodology then presents a comprehensive approach to find the best ranking among the alternative suppliers of a typical product. A hybrid modified TOPSIS is integrated with a preemptive goal programming model in this study and then compared to an analytical hierarchy process (AHP) to show the effect of considering interdependencies in the supplier selection process. The results indicate that the proposed methodology provides a higher total value of purchasing (TVP) than AHP while the total cost of purchasing (TCP) of both methods are equal. Empirical proof is offered based on a case study.

Multi-objective model for multi-period, multi-products, supplier order allocation under linear discount

In this paper, a multi-objective mixed integer nonlinear programming model is proposed to solve the supplier order allocation problem. We investigated a problem where a single buyer orders multiple products from multiple suppliers in multiple periods. The model takes into account the linear discount pricing scheme, the suppliers' capacity limits, the delivery rate and the quality of the items, the minimum order quantities, and the budgetary limitations. The buyer should decide on how to allocate orders optimally between selected suppliers to maximize the total value of purchase while minimizing the total cost of purchase simultaneously. Finally, two numerical examples in discount and non-discount environments are given to illustrate the application of the model. The results show that order values can be largely influenced by supplier linear discount.

Global supplier selection considering sustainability and carbon footprint issue: AHP multi-objective fuzzy linear programming approach

With growing concern about environmental protection, carbon emission has become an important factor for global supplier evaluation. Most of the earlier models have focused on cost, quality, geographical location, risk, etc., issues but not given enough importance to carbon emission for global supplier evaluation. Few studies have addressed sustainability but not succeeded to quantify carbon footprint for outsourcing. This paper quantifies the outsourcing carbon footprint that is used as objective function in multi-objective fuzzy linear programming for global supplier evaluation and quota allocation. As specific contribution, different carbon management factors and outsourcing carbon cap are introduced in the model. In multi-objective formulation, total cost, quality rejection, late delivered item, carbon footprint, and total value of purchasing (TVP) are considered as five objectives that have to be optimised simultaneously. AHP is used to calculate the performance of suppliers’ on qualitative criteria. ...

Integrating fuzzy TOPSIS and multi-period goal programming for purchasing multiple products from multiple suppliers

In this paper, a two-phase approach for supplier selection and order allocation problem under a fuzzy environment is proposed. We investigate a problem in which a single buyer orders multiple products from multiple suppliers in multiple periods. To account for inherent ambiguity and vagueness in most real-world data and information, in the first phase of the approach, a fuzzy multiple criteria decision making (FMCDM) method is used to obtain the overall ratings of alternative suppliers, and to select the most qualified ones for further evaluations. In the second phase, using the goal programming (GP) technique, we construct a multi-objective mixed integer linear programming (MOMILP) model to determine the order quantities of each selected supplier for each product in each period. In the MOMILP model, two goals are considered: 1) total value of purchasing (TVP) and 2) meeting the total available periodic budget. Constructing the approach in this way effectively reduces the risk of purchasing. This is because besides evaluating suppliers with regard to a set of quantitative and qualitative criteria, there is also a systematic way to purchase from more than one supplier. Finally, a numerical example is conducted to clarify the proposed approach and to show its usefulness.

Application of AHP and ANP in supplier selection process-a case in an automotive company

Most organizations prefer to outsource the activities which are not cost-efficient. With regard to the huge amount ofexpenditure in this area, proper selection of the desirable suppliers becomes significant. Previous studies indicated that the criteriaof supplier selection might not be always independent, and this fact implies the existence of interdependencies among them that mayaffect the supplier selection. This study presents and compares two multi-attribute decision making (MADM) techniques to dealwith the supplier selection problem with and without interdependency. An Analytic Hierarchy Process (AHP), and its extension,Analytic Network Process (ANP) are applied to find the final priorities of the suppliers respectively for the cases of independencyand interdependency in an automotive manufacturing company. The two techniques lead to different rankings for the potentialsuppliers. Thus, a Preemptive Goal Programming (PGP) with two goals, maximizing the Total Value of Purchasing and minimizingthe Total Cost of Purchasing, to decide which method is the best was conducted. The whole process is illustrated in a case study.The results from the company of the case study showed that the ANP had the optimal TCP of 1,290 US dollars, while the valuefor AHP was 1,710 USD. However, comparing the TVP value for the two methods shows a negligible difference.

AHP approach for supplier evaluation and selection in a steel manufacturing company

Supplier selection is one of the most critical activities of purchasing management in supply chain. Supplier selection is a complex problem involving qualitative and quantitative multi-criteria. A trade-off between these tangible and intangible factors is essential in selecting the best supplier. The work incorporates AHP in choosing the best suppliers. The results suggest that AHP process makes it possible to introduce the optimum order quantities among the selected suppliers so that the Total Value of Purchasing (TVP) becomes maximum. In this work, an AHP-based supplier selection model is formulated and then applied to a real case study for a steel manufacturing company in Malaysia. The use of the proposed model indicates that it can be applied to improve and assist decision making to resolve the supplier selection problem in choosing the optimal supplier combination. The work represents the systematic identification of the important criteria for supplier selection process. In addition, the results exhibit the application of development of a multi-criteria decision model for evaluation and selection of suppliers with proposed AHP model, which by scoring the performance of suppliers is able to reduce the time taken to select a vendor.

Integrated analytical hierarch process and mathematical programming to supplier selection problem with quantity discount

In this article an integration of analytical hierarchy process and non-linear integer and multi-objective programming under some constraints such as quantity discounts, capacity, and budget is applied to determine the best suppliers and to place the optimal order quantities among them. This integration-based multi-criteria decision making methodology takes into account both qualitative and quantitative factors in supplier selection. While the analytical hierarchy process matches item characteristics with supplier characteristics, non-linear integer programming model analytically determines the best suppliers and the optimal order quantities among the determined suppliers. The objectives of the mathematical models constructed are maximizing the total value of purchase (TVP), minimizing the total cost of purchase (TCP) or maximizing TVP and minimizing TCP simultaneously. In addition, several “what if” scenarios are facilitated and the quality of the resulting models is evaluated on real-life data.

An integrated approach of Analytic Hierarchy Process and Fuzzy Linear Programming for supplier selection

Supplier selection is a Multi-Criteria Decision-Making problem in a supply chain involving many qualitative and quantitative factors. In this paper, an integrated approach using Analytic Hierarchy Process (AHP) and Fuzzy Linear Programming (FLP) is adopted for supplier selection and quota allocation problem. AHP is used to rate the suppliers, while FLP is used to allocate the quota to the suppliers. In FLP, multiple conflicting objectives with some constraints of buyers and suppliers are considered to optimise the order quantities. The ratings of suppliers, which are outputs of AHP, are used as inputs for Total Value of Purchase (TVP) where TVP is one of the objectives of FLP. Finally, sensitivity of the method has been analysed to understand the effect of variation in priority of selection criteria on suppliers' rating and then on quota allocation.

Multi-period lot-sizing with supplier selection using achievement scalarizing functions

In this paper, an integration of Analytic Network Process (ANP) and achievement scalarizing functions is proposed to choose the best suppliers and define the optimum quantities among the selected suppliers by considering tangible–intangible criteria and time horizon. To reflect the decision maker’s (DM’s) preferences more accurate, an additive achievement function is defined consist of several components. In this additive function while unwanted deviations from periodic budget and aggregate quality goals are balanced by Minmax Goal Programming (MGP), and unwanted deviations from total cost, total value of purchasing (TVP) and aggregate quality are minimized by Achimedean Goal Programming (AGP) to provide more acceptable solutions. This multi-period model enables us to reflect DM’s preferences more flexible than the other traditional models that use only one type of achievement function. The sensitivity analysis was also performed for different levels of periodic demands. It is also possible to enlarge the sensitivity analyses for other parameters such as different levels of capacity, and different weights of components.

An integrated multi-objective decision-making process for multi-period lot-sizing with supplier selection

Supplier selection is a multi-criteria problem which includes both tangible and intangible factors. In these problems if suppliers have capacity or other different constraints two problems will exist: which suppliers are the best and how much should be purchased from each selected supplier? In this paper an integrated approach of analytic network process (ANP) and multi-objective mixed integer linear programming (MOMILP) is proposed. This integrated approach considers both tangible and intangible factors in choosing the best suppliers and defines the optimum quantities among selected suppliers to maximize the total value of purchasing (TVP), and to minimize the total cost and total defect rate and to balance the total cost among periods. The priorities are calculated for each supplier by using ANP. Four different plastic molding firms working with a refrigerator plant are evaluated according to 14 criteria that are involved in the four clusters: benefits, opportunities, costs and risks (BOCR). The priorities of suppliers will also be used as the parameters of the first objective function. This multi-objective and multi-period real-life problem is solved by using previous techniques and a reservation level driven Tchebycheff procedure (RLTP). Finally the most preferred nondominated solutions are determined by considering the decision maker's (DM's) preferences and the results obtained by these techniques are compared.

Analytic network process and multi-period goal programming integration in purchasing decisions

This paper presents a multi-period inventory lot sizing scenario, where there is single product and multiple suppliers. By considering multi-period planning horizon, an integrated approach of Archimedean Goal Programming (AGP) and Analytic Network Process (ANP) is suggested. This integrated approach proposes a two-stage mathematical model to evaluate the suppliers and to determine their periodic shipment allocations given a number of tangible and intangible criteria. In the evaluation stage, the suppliers are evaluated according to 14 criteria that are involved in four control hierarchies; benefit, opportunity, cost and risk (BOCR). In the shipment stage, a multi objective mixed integer linear programming (MOMILP) model is described to solve the order allocation problem. This MOMILP model is suggested to achieve target values of periodic goals: budget, aggregate quality, total value of purchasing (TVP) and demand over the planning horizon, without exceeding vendor production capacities. This multi-period model is solved by using AGP. Finally some computational experiments are conducted to test the performance of the proposed method.

A DECISION SUPPORT SYSTEM FOR SUPPLIER SELECTION PROCESS

Today's global business environment, characterized by unprecedented competitive pressures and sophisticated customers that demand speedy solution creates a bigger set of potential suppliers to evaluate and to choose from. To deal with the complexities of the supplier selection process, an integration of Quality Function Deployment (QFD), Analytical Hierarchy Process (AHP) and Preemptive Goal Programming (PGP) techniques is proposed. A QFD matrix is used to display the degree of relationship between each pair of requirement for suppliers and supplier evaluating criterion. This paper employs the AHP first to measure the relative importance weighting for each of the requirements in the QFD process. Secondly, it is used to assess the evaluating score for each of the candidate suppliers for each particular supplier-evaluating criterion. PGP is built to deal with some suppliers' constraints such that the total value of purchase (TVP) becomes maximum and the total cost of purchase (TCP) minimum.

A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming

Supplier selection is a multicriteria problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is necessary to make a trade off between these tangible and intangible factors some of which may conflict. When capacity constraints exist, this problem becomes more complicated as, in these circumstances, managers should decide about two problems: which suppliers are the best and how much should be purchased from each selected supplier. Some authors have applied mixed integer, goal and multi-objective programming to solve this problem. As these techniques are mathematical, they have significant problems in considering qualitative factors which are very important in supplier selection, especially when supplier partnership is desired. In this article an integration of a analytical hierarchy process and linear programming is proposed to consider both tangible and intangible factors in choosing the best suppliers and placing the optimum order quantities among them such that the total value of purchasing (TVP) becomes maximum. This model can be applied to supplier selection with and without capacity constraints. A numerical example is presented and the model advantages are discussed.