This study provides an overview of the fuzzy TOPSIS and Multi-Choice Goal Programming (MCGP) methods for Multi-Criteria Decision-Making (MCDM) problem under uncertain environments. Supplier selection is mostly a complex multi-criteria problem which consists of qualitative and quantitative criteria. Those criteria should be considered advertently as a final decision in comprehensive and objective supplier selection as well. This study deal with the optimum decision making for selecting supplier and allocating order by applying the proposed method of integrated fuzzy TOPSIS and MCGP (Multi-Choice Goal Programming). To deal with the uncertain and imprecise judgment of decision makers, a Fuzzy TOPSIS is utilized to express it by triangular fuzzy numbers. The final supplier selection and order allocation are obtained by integrating the closeness coefficients to the MCGP model. A numerical example is given to clarify the main results developed in this paper

In the current global market, managing supply is not a straightforward process and it becomes even more complex as uncertainty and disruptions occur. In order to mitigate their impact, the selection of suppliers of strategic items should have a more holistic view of the operations in the supply chain. We propose an integrated model for supplier selection, considering inventory management and inbound transportation. We approach this problem, incorporating stochastic demand and suppliers' imperfect quality. Imperfect quality triggers additional costs, including external failure and holding costs. Supply disruptions also affect the suppliers' lead time, resulting in delivery delays. We develop a methodology to address this challenge with simulation-optimisation. A genetic algorithm determines supplier selection decisions, while inventory decisions are computed analytically. Discrete-event simulation is used to evaluate the overall performance, as well as to update the lead time dynamically, according to the disruptions. Finally, sensitivity analysis providing managerial insights reveals that criteria in supplier selection should be given a different priority depending on the characteristics of the items, and the effectiveness of disruption mitigation strategies depends on the disruption characteristics.

This paper presents a review on selection problem of material handling equipment (MHE) and general equipment used in industry area. The issue on MHE is widely paid attention since MHE has contribution on material, good and product accomplishment. Few methods and softwares have been proposed and developed to select the most appropriate MHE for a complex selection problem. Today’s high diverisity of MHE categories and types influence the generation of many possible choices which leads to the complexity. In this paper, a further discussion in terms of MHE and equipment including three major points namely level of selection, the context of selection problem and the approaches are served to highlight the complex MHE selection according to the number of possible choices provided, to analyse the consideration for the problem context, and to reveal the superior method for complex MHE selection. Forty-two papers collected from the past study are presented asscociating each point of the discussion.

Companies must be able to identify their suppliers appropriately and effectively in order to survive in the competitive market conditions. In order to fulfill and surpass the expectations of the consumers and clients, companies need to interact with the relevant suppliers. It is a tough manner for companies to select the best supplier from a large number of relevant alternatives. The selection process of the appropriate supplier involves multiple interacting and competing factors. Generally, the selection process and its results cause a waste of time and money. For this purpose, MCDM methodologies are utilized to manage this complex process efficiently. MCDMs allows for consistent and accurate decision-making as well as the selection of the most appropriate supplier. MCDM is one the most preferred tool to select the best alternative under the conflicting and competitive criteria when the evaluations are made in crisp numbers. Therefore, MCDM methods are preferred in various applications in academia and real life. However, the evaluations could not be always possible with crisp numbers, especially in vague environments or evaluations needs qualitative data. This study is one of the first to combine the AHP and COPRAS supplier selection methods with interval-valued Pythagorean fuzzy (IPF) logic. The effectiveness of these IPF-AHP and IPF-COPRAS evaluations for the supplier selection problem is compared and examined. The experimental results of case scenarios show that IPF is an effective way to apply in decision-making applications. In addition, sensitivity analysis is conducted to evaluate the proposed methodologies. According to sensitivity analysis, the IPF-AHP and IPF-COPRAS be able to illustrate the effects of small changings in criteria weights. Therefore, companies can use the IPF-AHP and IPF-COPRAS to assist their decision-makers in identifying and selecting the best suppliers.