A Model for Allocating Orders to Suppliers in Case of Quantity Discounts

One of the most important activities in the management of input items of a company is focusing on the process of purchasing, supplier selection and allocating order to suppliers. Decisions about supplier selection due to simultaneously taking inconsistent and diverse issues into account in a wide range of strategic to operational factors, and from quantitative to qualitative criteria will be complex by nature. 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 business volume discounts exist, this problem becomes more complicated. In this paper a multi-objective model for order allocation under volume discount conditions is presented. In this context, suppliers offer price discounts on total business volume. A solution methodology is presented to solve the multi-objective model, and the model is illustrated using a numerical example. Studying various combinations of constraints such as capacity, timely delivery, disadvantages and cost, taking into account quantity discounts, considering the weight of the suppliers in order allocation and integration of these cases with each other, have made the current research quite unique

An integrated model for sustainable supplier selection and multi-period multi-product lot-sizing for packaging film industry in Iran

The emergence of sustainability issues has created increasing interest among those involved in the field of sustainable supply chain management. Companies are motivated to modify their supply chains activities based on sustainability issues to enhance their overall level of sustainability in order to fulfil demanding environmental and social legislation and to deal with increasing market forces from different stakeholder groups. Within supply chain activities, selecting appropriate suppliers based on the criteria of sustainability, e.g., economic, environmental, and societal might help companies move towards sustainable development. Although several studies have been accomplished to incorporate sustainability criteria into supplier selection problem, little attention has been paid to developing a comprehensive mathematical model that allocates the exact quantities of orders to suppliers considering lot-sizing problems. Moreover, the effect of inflation as an important issue for companies in the developing countries has been neglected in studies that examined multi-period multi-product lot-sizing along with supplier selection. In this study, a multi-objective mathematical model for sustainable supplier selection integrated with multi-period multi-product lot-sizing problem under the effects of inflation was developed. The model consists of four objective functions which are minimizing total cost, maximizing total social, total environmental score, and total economic qualitative scores. The mathematical model was developed based on the parameters discovered by preprocessing the social, environmental, and economic data of suppliers using a rule-based-weighted fuzzy approach and fuzzy analytical hierarchy process. The model attempted to simultaneously balance different costs under inflationary conditions to optimize the total cost of purchasing and other objective functions. A comprehensive framework was developed as a road map for procurement organizations in order to facilitate the allocation of optimal order quantities to suppliers in a sustainable supply chain. The proficiency and applicability of a proposed approach was illustrated using a case study of packaging films from the food industry. For each main criterion of sustainability, their related subcriteria and influencing factors were extracted from literature and the most related ones were selected by company’s experts. In this research, green competencies, environmental management system, pollution, occupational safety and health, training and education, contractual stakeholder, economic qualitative, and cost were selected by company’s experts as the main subcriteria of sustainable supplier selection. The consideration of sustainability criteria in the proposed multi-objective model revealed that a higher value of sustainable purchasing can be achieved in comparison with a single objective costbased model. In addition, the results show that the proposed model can provide a purchasing plan for the company while monitoring the effect of inflation and assuaging its concerns regarding sustainability issues

Wood-based construction project supplier selection under uncertain starting date

There is a growing interest in supply management systems in today's competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers' control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this paper, we address the supplier selection problem (SSP) in wood-based construction industry (housing projects) in the presence of project commencement uncertainties. Based on the suppliers' (vendors') reaction towards these uncertainties in the delivery time, we explore two cases: (a) supplier selection with buyer penalty for a delay (SSPD) where the price of product increases with the delay; (b) supplier selection with quantity reduction for a buyer delay (SSQRD). Three heuristic-based supplier selection approaches are proposed and tested on randomly generated data sets. The proposed approaches show promising result

Order allocation in a multiple-vendor and quantity discount environment: A multi-objective decision making approach

Integrated supplier selection and order allocation is a complex problem that is important for both designing and operating supply chains. It becomes especially complicated when quantity discounts are considered at the same time. Under such circumstances, most studies often formulate the problem as a Multi-Objective Linear Programming problem (MOLP), and then transform it to a Mixed Integer Programming problem (MIP) to handle the inherited multi-objectives, simultaneously. But, objectives are not of equal importance and in this approach scaling and subjective weighting often are not considered. In addition, some of the studies that use weighting method to solve the MOLP, usually ignore to normalize the coefficients. However, as different coefficients have different units such as cost or number coefficients, so weighted summation will be meaningless. Furthermore, in most of the studies only quantitative criteria are considered in mathematical model. But, the importance of some qualitative criteria persuade decision maker to consider other affective criteria as well as cost. In this study, in order to ease the problem and to obtain a more reasonable compromised solution for order allocating among suppliers, an integration of analytical hierarchy process and linear integer and multi-objective programming is proposed. The large number of criteria and attributes are employed in this problem and they are employed in a comprehensive model to solve the multi-objective problem and to find the most preferred non dominated solutions by considering decision maker’s (DM) preferences. Some illustrative examples are solved using LINGO and the results are compared. The sensitivity analysis and comparing the results with one of the well-known studies in the literature has demonstrated the flexibility and efficiency of the proposed model to deal with large sized problems and incorporate different purchasing policies, easily and in a short amount of time

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Supplier selection problem ; an approach using genetic algorithms

This research tackles a supplier selection problem composed of different suppliers with limited capacities, a client with deterministic multi-period demands and specific allowed inventory limit in each period for a single product. The objective is to select the most economical set of suppliers in order to meet the client's demand. A novel genetic algorithm and chromosome representation are proposed to find near optimal solutions. The performance of the proposed algorithm is compared with the exact approach using randomly generated data sets. In this supplier selection problem, initially proper population size is determined for three different problem sizes of small, medium and large; as the next step of the experiments, proper numbers of iterations for each problem size are found; finally, different mutation probabilities are tested for different problem sizes and the best mutation probabilities for each problem size are selected based on the calculated error. By the help of the results of the experiments and gathered information, proper population size, number of iterations, and mutation probabilities are recommended for problems with similar size and constraints. Key words: Supply Chain Management, Supplier Selection, Genetic algorithms, Optimizatio

Managing Supply for Construction Project with Uncertain Starting Date

There is a growing interest in supply management systems ¬¬in today’s competitive business environment. Importance of implementing supply management systems especially in home construction industry is due to the fact that several risks arising from different sources can adversely affect the project financially or its timely completion. Some risks of construction projects are out of managers’ control while other risks such as supply related ones can usually be controlled and directed by effective managerial tactics. In this thesis, we address the supplier selection problem (SSP) in wood-base construction projects in the presence of project commencement uncertainties. The project could be delayed for any reason and thus materials required for the project may not be needed on the promised date, however, pursuing the supplier for new delivery date may not be easy and without risk. Accepting the delivery before the project commencement date will be again a costly option because of the high holding cost. In this thesis, we present two problem cases and present heuristic based solution approaches. In the first case we assume that price of the product increases with the delay. In the second case we assume that promised quantity at the agreed price reduces with the delay. The proposed approaches are tested on the randomly generated data set and compared with the optimal solutions. The problems considered in this research are novel and the proposed approaches deal with the important and common risks in construction industry in order to achieve a robust supply chain. The solution approaches presented in this thesis can be applied to different industries to improve the quality and efficiency of supplier-buyer collaborations

Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process

Within supply chains activities, selecting appropriate suppliers based on the sustainability criteria (economic, environmental and social) can help companies move toward sustainable development. Although several studies have recently been accomplished to incorporate sustainability criteria into supplier selection problem, much less attention has been devoted to developing a comprehensive mathematical model that allocates the optimal quantities of orders to suppliers considering lot-sizing problems. In this research, we propose an integrated approach of rule-based weighted fuzzy method, fuzzy analytical hierarchy process and multi-objective mathematical programming for sustainable supplier selection and order allocation combined with multi-period multi-product lot-sizing problem. The mathematical programming model consists of four objective functions which are minimising total cost, maximising total social score, maximising total environmental score and maximising total economic qualitative score. The proposed model is developed based on the parameters achieved through the preprocessing of suppliers’ social, environmental and economic data by a rule-based weighted fuzzy approach and fuzzy analytical hierarchy process. The proficiency and applicability of the proposed approach is illustrated by a case study of packaging films in food industry. Considering sustainability criteria in the proposed model reveals that a higher value of sustainable purchasing is achievable in comparison with a single-objective cost-based model