A modified variable neighborhood search algorithm for dynamic lot-sizing with supplier selection under varying delivery time quotation

In this study, a research model for selecting a PL product supplier was established through prior research related to supplier selection and interviews with experts. It is intended to identify the importance of the main attributes and components that distribution company's PL development buyers consider important in selecting a product supplier and present strategic implications to product suppliers. Since it is more appropriate to survey experts in a specific specialized field rather than an unspecified number, the analysis was conducted using the AHP technique. This study targeted 20 buyers of distributors, a group of experts who develop PL products and select suppliers in the actual distribution field. A total of 20 surveys met all consistency of 0.1 or less and were used for the study. As a result of the study, the importance ranking of PL product development buyers' selection of suppliers was in the order of price factor, quality factor, technology factor, financial factor, and relationship factor, and the price and quality aspect that the distribution industry prioritized was the most important. In particular, this study examined the importance by classifying them into fresh food, processed food, and non-food according to the items operated by each buyer, and it was confirmed that the important factors thought of by PL product development buyers were different according to the characteristics of the product group being operated. The price factor is the most important recognition factor by PL product development buyers handling fresh and processed food, and the quality factor is the second most important factor. On the other hand, PL product development buyers handling non-food products showed the result of prioritizing quality factors over price factors. Third, technical factors were considered important, and relatively, the financial factors and related factors of suppliers were of very low importance in relation to the selection of suppliers. This study empirically analyzed the factors that are considered important in the decision-making process related to the selection of PL product suppliers by PL product development buyers, and it can be said to be meaningful in that it provides a direction for what strategies suppliers should have to cooperate with distributors. The point is that PL product suppliers should recognize and prepare the priorities of factors that PL product development buyers think of depending on the items they want to supply. In addition, if PL product suppliers identify and prepare the priorities and detailed items of the selection factors for each item, PL product development buyers will be able to have a comparative advantage over competitors in selecting PL product suppliers.

The decision-makers in manufacturing industries continuously optimize every supply-chain part to achieve optimal profit. In this paper, three crucial activities in the supply chain are observed as profit contributors: supplier selection, inventory management, and production planning. Decision-making support is needed to optimize those activities, especially when prices/costs involve discounts. Therefore, this study aims to develop integrated decision-making support for supplier selection, inventory management, and production planning involving discounted prices. The problem was considered with multi-supplier, multi-raw material, multi-product, and multi-observation time instant. The objective was based on maximizing the profit for the entire activity, i.e., from the raw material procurement and storage to the production. This supply chain was modeled as mixed-integer linear programming with a piecewise objective function representing the profit, which was maximized. It was also modeled with a bunch of constraint functions, including product demand satisfaction. The proposed model was tested with computational simulations using randomly generated supply chain data. The primal simplex algorithm was also employed to calculate the real value of the optimal decision, which was combined with the Branch-and-Bound approach to calculate the appropriate integer solution. The results showed that the optimal decision was achieved, namely (1) The optimal quantity of raw materials ordered to each supplier, (2) The optimal production quantity, and (3) The optimal inventory level, which provided the maximal profit for the whole optimization time horizon. This indicated that the proposed decision-making support model is implementable for industrial decision-makers.

Applying supplier selection methodologies in a multi-stakeholder environment: A case study and a critical assessment

Nowadays, shareholders are being encouraged to enhance supply chain risk management in order to deal with several disruptive and operational risks. Producing spice and flavor is one of the high-risk industries as the main raw material is spice and its quality is variable and strongly depends on suppliers, seeds, and climate. Having a constant quality of spices and producing a flavor that satisfies every customer’s demand is intricate. Therefore, these companies encountered a variety of goods which increased complexity and uncertainty in supply, processing time, and demand. To come up with risks and uncertainties, in this paper a robust bi-objective multi-product mathematical model is developed to consider resiliency and uncertainty in a multi-period, multi-item supply chain network design simultaneously. The first objective function maximizes total profits when the second one maximizes the total score of resiliency in which Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) have been used to obtain the four resiliency factors weights for the objective function. We proposed an approach for making coordination between production planning, distribution, supplier selection, and order allocation in a flavor plant. The -constraint method is used to obtain Pareto solutions for a real case in Iran. Finally, sensitivity analysis has been done for tracking the trade-off between optimization and robustness with different robust parameters and investigating unmet demand and benefits of resilience consideration.

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.

Economic lot sizes and vehicle scheduling

Supplier selection is an important problem in supply chain management. In practice, it is common for a purchasing company to procure a bundle of products simultaneously. In this regard, synergy effect could exist between products and hence affect the final choice of suppliers. It is therefore necessary to incorporate the synergy effect between products in supplier selection process. Agent-based negotiation models are applied to automate supplier selection process. Negotiation protocol is an essential component should be considered when building an effective agent negotiation model. The objective of this research is to propose a negotiation protocol special for multi-product supplier selection problem. The negotiation protocol is a hybrid multi-agent protocol of combinatorial procurement auction protocol and multi-bilateral bargaining protocol. The negotiation protocol is able to support the purchasing company and suppliers negotiate on the concrete commitments of multiple products simultaneously, and select suppliers for multiple products. In addition, both the purchasing company and suppliers can express their preferences on the synergy effect between products in negotiation process by adopting the negotiation protocol. Simulation is conducted to demonstrate the effectiveness and efficiency of the negotiation protocol.

Today, business organizations are facing increasing pressure from a variety of sources to operate using sustainable processes. Thus, most companies need to focus on their supply chains to enhance sustainability to meet customer demands and comply with environmental legislation. To achieve these goals, companies must focus on criteria that include CO2 (carbon footprint) and toxic emissions, energy use and efficiency, wastage generations, and worker health and safety. As in other industries, the food processing industry requires large inputs of resources, which results in several negative environmental effects; thus, decision-makers have to evaluate qualitative and quantitative factors. This work identifies the best supplier for edible oil production in the small and medium enterprise (SME) food processing industry in Vietnam. This study also processes a hybrid multicriteria decision-making (MCDM) model using a fuzzy analytical hierarchy process (FAHP) and green data envelopment analysis (GDEA) model to identify the weight of all criteria of a supplier’s selection process based on opinions from company procurement experts. Subsequently, GDEA is applied to rank all potential supplier lists. The primary objective of this work is to present a novel approach which integrates FAHP and DEA for supplier selection and also consider the green issue in edible oil production in uncertain environments. The aim of this research is also to provide a useful guideline for supplier selection based on qualitative and quantitative factors to improve the efficiency of supplier selection in the food industry and other industries. The results reveal that Decision-Making Unit 1 (DMU 1), DMU 3, DMU 7, and DMU 9 are identified as extremely efficient for five DEA models, which are the optimal suppliers for edible oil production. The contributions of this research include a proposed MCDM model using a hybrid FAHP and GDEA model for supplier selection in the SME food processing industry under a fuzzy environment conditions in Vietnam. This research also is part of an evolution of a new hybrid model that is flexible and practical for decision-makers. In addition, the research also provides a useful guideline in supplier selection in the food processing industry and a guideline for supplier selection in other industries.

Joint production planning, pricing and retailer selection with emission control based on Stackelberg game and nested genetic algorithm

PurposeRefractory materials are now used in all major industries that demand high-temperature resistance, including petrochemicals, steel, cement and aviation. Businesses must decrease operating costs, enhance product technology, sell well and manage corporate risks in decision-making, notably supplier selection, to be more competitive. The study aims to determine the key criteria and factors of supplier selection and to evaluate the importance of the key factor of the supplier selection criteria for the refractory materials manufacturers in Taiwan.Design/methodology/approachAnalytical hierarchy process (AHP) is used to rank these factors for the decision maker. The AHP method is suitable for verifying refractory supplier selection criteria and providing references. The weighted loss scores for each supplier are then determined using the relative importance as the weights. Supplier selection criteria are ranked using their aggregate weighted loss scores. The provider with the lowest loss score should be chosen.FindingsProduct quality is the most significant of the five criteria: product quality, production technology, logistics capacity, service capability and supplier background. Professionalism is the most significant aspect of product quality, whereas equipment and capacity are vital in manufacturing techniques. The studies also show that the delivery rate is essential for logistics and service capabilities.Practical implicationsThis research has important implications for refractory suppliers in promptly fine-tuning the production and service to enhance customer satisfaction, which is key to business sustainability.Originality/valueThe application of an AHP technique to a real-world industrial issue is what makes this research unique. This research addressed one of the most critical topics in supply chain operations by offering better judgement for supplier selection via the use of suitable quantitative methodologies.

Lead Time (LT) is one of the most important factors that affect all participants in business systems, especially manufacturing/production systems. In practice, effective management of Supply Chain (SC) needs to make proper decisions about supplier selection, transportation mode selection, production planning, etc., with LT as an important measure. In this paper, the effect of LT statistical specifications on SC performance under uncertainty is investigated and the two popular statistical distributions of LT (uniform and normal distributions) are compared. The outcome of this study corresponds to some guidelines in selection of supplier, transportation mode and appropriate planning of production system regarding LT.

In this paper, we study the dynamic lot-sizing problem with demand time windows and container-based transportation cost. For each particular demand, there are corresponding earliest and latest times, and the duration between such earliest and latest times is the demand time window. If a demand is satisfied by a delivery within demand time window, then there is no holding or backlogging cost incurred. Our purpose is to satisfy demand at a minimum total cost, including setup cost, procurement cost, container cost, and inventory holding cost.

INTRODUCTION In this paper, we present the theory of connection (ToC) based approach for formulation of mathematical model of material flow processes. The major advantage in using the theory of connection is that, the same set of functions (or procedures) can be used for formulation of mathematical models of many engineering and management processes (Bjorke, 1995; Davidrajuh, 2000). Theory of connection (ToC), previously known as manufacturing system theory, in the form it is presented here, is due to the work of the Scandinavian School of Systems Theory for the past 30 years; for detailed study of ToC, interested readers are referred to Bjorke (1995). The idea behind ToC is to bring geometry and algebra together: first, geometric modeling is used to model physical phenomena, and then a set of algebraic equations are drawn out of the geometric model, so that by using a computer these equations could be solved. The usefulness of ToC is that, different subsystems of different disciplines can be modeled and integrated by performing the same procedure; this is very important for fields like e-commerce as e-commerce involves diverse disciplines like manufacturing, business management, supplier selection, etc. MODELING APPROACH BASED ON ToC First, the concept of system model is introduced; this is done with the help of a simple electrical network known as the inductor-resistor-capacitor (LRC) network. Then, the simple LRC system model is mapped into the geometrical space with the help of properties matrix. System Model A system consists of three fundamental components, such as elements, connections, and sources. The elements carry all the physical or economical properties of the system. Elements are the building blocks of the physical system. For example, in a LRC network, the resistors, capacitors and inductors are the elements; the property of a resistor is its admittance, whereas a machine element's property could be its processing time, ratio between input items and output items, scrap percentage etc. When there is no connection between the elements, the set of isolated elements is called the primitive system. The connections reflect how the elements influence each other and it represents the structure of the system. The set of connected elements is called the connected system. Finally, the sources reflect the influence between the total system and the environment. Sources are the environment's influence on the system; in an electrical circuit, source s could be current or voltage sources; in production planning, demand of products, startup-setup times, costs involved are some of the sources. Geometrical Spaces, Vectors, and Matrices ToC is based on the use of continuous geometrical 3-space or more typically an n-space volume (a Euclidean space [R.sup.n]). A vector (called a contravariant vector) represents a point in the Euclidean space, or primary space, from the origin to the point; A vector in a 3-space is represented by: x = [x.sup.1][[epsilon].sub.1] + [x.sup.2][[epsilon].sub.2] + [x.sup.3][[epsilon].sub.3], where ( [[epsilon].sub.1],[[epsilon].sub.2],[[epsilon].sub.3]) is the basis vector along the three axes. Whereas, a point (called a covariant vector) in the corresponding dual space of the vector space, defines another vector which can be represented by: a = [a.sub.1][[epsilon].sup.1] + [a.sub.2][[epsilon].sup.2] + [a.sub.3][[epsilon].sup.3], Where ([[epsilon].sup.1],[[epsilon].sup.2],[[epsilon].sup.3]) is the basis co-vector along the three axes. A property matrix keeps properties (or characteristics) of primitive elements, whereas a connection matrix represents the connections between the primitive elements. TOOLBOX OF FUNCTIONS The process of mathematical modeling and simulation approach based on ToC is traditionally done by a toolbox of functions implemented in APL (A Programming Language). …

Sustainable supplier selection is a key strategic problem in supply chain management. The aim of this research is to provide a new hybrid multicriteria model for evaluating technology suppliers and validate it with a case study in the banking sector. This approach allows companies to perform qualification, selection, ranking and sorting of suppliers on a sustainable basis. Integration of several techniques is necessary to address this complex decision problem with conflicting economic, environmental and social criteria. Analytic hierarchy process (AHP) is useful for problem structuring and weighting criteria collaboratively. Multi-attribute utility theory (MAUT) is applied to obtain indicators for product quality and supplier risks, whose utility functions are derived by data-driven models that favour evaluation objectivity and transparency. Preference ranking organisation method for enrichment evaluation (PROMETHEE) is suitable for supplier selection due to its discriminant power among alternatives. Finally, FlowSort is proposed to classify suppliers into ordered groups and the outcomes are compared with results from MAUT. Results show its applicability by increasing process transparency and reducing operational risks in practice.

Supplier selection problems have been considered widely in literature; however, considering the availability and reliability of the products provided by suppliers has been investigated less. In this regard, the presented work addresses a supplier selection problem in which the reliability of the parts is one of their main factors for supplier selection. This paper develops a multiobjective mathematical goal programming model to allocate the system’s components orders to the suppliers. The model minimizes the system construction costs and maximizes the probability of working the system in nominal and half capacity. The similarity of the ordered components affects their delivery lead times and prices. The model determines the optimal solution for an industrial system composed of 4 parts. The proposed approach includes using the reliability block diagram to develop the Markov chain model. A multiobjective binary nonlinear mathematical program uses the Markov model to select the optimal components suppliers. Solving the model by goal programming approach provides the possibility of reflecting the decision-maker opinion relative to the construction cost’s importance compared to system availability.