A comparative study of multiple-criteria decision-making methods under stochastic inputs

This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative

A regional information-based multi-attribute and multi-objective decision-making approach for sustainable supplier selection and order allocation

Although extant studies proposed various models and frameworks for sustainable supplier selection problems, they paid limited attention to the incorporation of regional economic, social, and environmental factors simultaneously for global supply chain design due to the difficulty in reflecting varies dimensions of the global business environment and their associated risk in a decision model. Existing supplier selection models also tend to focus on the formulation of a simplified supply chain structure rather than considering more realistic supply chain operations under multiple sourcing and product designs. To facilitate the complex decision-making process of global supplier selection problems, this study proposes an integrated approach that consists of two phases to effectively reflect the multi-perspectives of global supply chain design for sustainability. The first phase identifies sustainable supplier regions through multi-attribute utility theory, considering four regional sustainability indices for economic and social factors in global business and logistics, to reflect the decision maker\u27s risk attitudes on global business opportunities. In the second phase, a multi-objective integer linear programming model for multiple sourcing and multiple product designs that minimizes economic and environmental objectives is applied to find optimal suppliers in the regions selected from the first phase and their order quantities. The proposed approach is illustrated through a bicycle supplier selection case study. The results show that the multi-objective sustainable decision under a multiple sourcing strategy for different product designs leads to a supply chain that is significantly different from the single-objective non-sustainable decisions. The case study under different decision scenarios shows that a decision maker should hold a balanced perspective under the multi-objective decision environment for sustainable supply chain design

A Design Process Framework to Deal with Non-functional Requirements in Conceptual System Designs

To simultaneously satisfy the user needs and project-specific technical requirements, it is imperative that complex engineering systems are designed using contemporary, systematic approaches. This study presents a framework that combines Axiomatic Design and Fuzzy Analytic Hierarchy Process to ensure that designers can concurrently satisfy the functional and non-functional requirements along with the design constraints of conceptual system designs. A conceptual design case of an autonomous battery charging system for Unmanned Aerial Vehicles is presented as an illustrative case study. The results showed that the approach can aid decision-making processes by systematic evaluation and comparison of conceptual designs such that the selected solutions satisfy user needs whilst also realising both functional and non-functional requirements of the system

Lean and green approach: an evaluation tool for new product development focused on small and medium enterprises

SMEs are crucial for economic health in both high and low-income economies worldwide. In Brazil, they are responsible for around 50% of the national GDP. However, SMEs face considerable barriers such as difficulties in financing international activity, identifying opportunities and making appropriate contacts in their target markets. This paper investigates the adherence of both lean and green practices for the development of new products (NPD), as means to improve their efficiency (lean perspective) and manufacture environment-friendly products (green perspective). Through a systemic review, we present 16 lean and green enablers for NPD operations. These elements comprise a structure of building blocks to evaluate lean and green practices. Thus, we propose a model that ranks the incidence of these practices regardless of the NPD organization level. Using two MCDM tools: AHP and fuzzy-TOPSIS, each enabler is evaluated considering the SMEs context in Brazil. Firstly, AHP defines the relative importance of six SMEs' characteristics. Secondly, we applied an expansion of the TOPSIS technique, adequate when the values of each alternative are not clearly determined. Therefore, we organized a structured interview consisting of 96 evaluation questions for NPD stakeholders. We carried out this diagnosis in three companies from southern Brazil, analysing their NPD operations, which is useful to establish a future improvement agenda

Fuzzy Analytical Hierarchy Process for Supplier Selection: A Case Study in An Electronic Component Manufacturer

Supplier selection has become one of the essential effects on the entire electronic supply chain network to gain competitiveness. In the upstream supply chain, companies are able to achieve a high quality and value of products to reduce the potential risks from both internal and external stakeholders by selecting the right suppliers. The case study company produces a nano sim-card connector in which four different types of raw materials are processed into different parts. Currently, the case study company selects each raw material supplier based on its appraisal record. Nevertheless, the appraisal record is measured by the department of procurement. When candidate suppliers are categorized at the same level, the cost becomes the priority criteria to select the supplier, which increases the potential risks of, for example, the components defect rate, a penalty from clients, and a reduction in orders. This paper proposed a Fuzzy analytic hierarchy process (FAHP) model for the selection of raw material suppliers by collecting data from two of the company’s departments (procurement and engineering) and the clients to address qualitative and quantitative elements, uncertainty, and linguistic vagueness based on the company’s scenario in two parts. First, the main and sub-criteria can be weighted using a decision-maker (DM) to identify the level of importance. Second, the FAHP model also dealt with personal preferences and judgement so that the right supplier(s) for each raw material could be selected by collecting and computing the data from the respondents. Then, the sensitivity analysis is applied to observe how the decisions change when the model parameters in the top five sub-criteria change. The proposed model can offer better information and solutions for the DM in the case study company to differentiate the crucial main and sub-criteria and select the suitable raw material suppliers effectively

An integrated model for green partner selection and supply chain construction

Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply chain because the environmental performance of the whole supply chain is significantly affected by all its constituents. The paper presents a model for green partner selection and supply chain construction by combining analytic network process (ANP) and multi-objective programming (MOP) methodologies. The model offers a new way of solving the green partner selection and supply chain construction problem both effectively and efficiently as it enables decision-makers to simultaneously minimize the negative environmental impact of the supply chain whilst maximizing its business performance. The paper also develops an additional decision-making tool in the form of the environmental difference, the business difference and the eco-efficiency ratio which quantify the trade-offs between environmental and business performance. The applicability and practicability of the model is demonstrated in an illustration of its use in the Chinese electrical appliance and equipment manufacturing industry