Reverse Logistics Network Design with a 3-Phase Interactive Intuitionistic Fuzzy Goal Programming Approach: A Case Study of Covid-19 in Pathum Thani, Thailand

During outbreaks, a vast quantity of Infected Medical Waste (IMW) can be substantially generated in a short period, which poses a massive risk to medical personnel and surrounding communities. This study proposes an Intuitionistic Fuzzy Multi-Objective Multi-Period Mixed-Integer Linear Programming (IFMOMILP) model for effective IMW management in outbreaks under uncertainty, considering financial and risk factors subject to a priority from Decision Makers (DMs). The primary emphasis is on determining the optimal locations and capacity levels for temporary facilities, including temporary storage and treatment centers, as well as the optimal transportation routes. A 3-phase interactive Intuitionistic Fuzzy Goal Programming (i-IFGP) approach is developed to solve this IFMOMILP model. First, the Jiménez approach is applied to handle the uncertainties. Then, the problem is solved by Intuitionistic Fuzzy Goal Programming (IFGP). An actual case study of the COVID-19 outbreak in Pathum Thani province in Thailand was carried out to demonstrate the effectiveness of the proposed approach. The proposed approach yields solutions with varying feasibility degrees and scaling factors, providing alternatives for DMs. Then, the score function is utilized to imply DMs’ satisfaction with the outcomes, which is a concrete measure since it can reflect the intention of the DMs

A Fuzzy Credibility-Based Chance-Constrained Optimization Model for Multiple-Objective Aggregate Production Planning in a Supply Chain under an Uncertain Environment

In this study, a Multiple-Objective Aggregate Production Planning (MOAPP) problem in a supply chain under an uncertain environment is developed. The proposed model considers simultaneously four different conflicting objective functions. To solve the proposed Fuzzy Multiple-Objective Mixed Integer Linear Programming (FMOMILP) model, a hybrid approach has been developed by combining Fuzzy Credibility-based Chance-constrained Programming (FCCP) and Fuzzy Multiple-Objective Programming (FMOP). The FCCP can provide a credibility measure that indicates how much confidence the decision-makers may have in the obtained optimal solutions. In addition, the FMOP, which integrates an aggregation function and a weight-consistent constraint, is capable of handling many issues in making decisions under multiple objectives. The consistency of the ranking of objective’s important weight and satisfaction level is ensured by the weight-consistent constraint. Various compromised solutions, including balanced and unbalanced ones, can be found by using the aggregation function. This methodology offers the decision makers different alternatives to evaluate against conflicting objectives. A case experiment is then given to demonstrate the validity and effectiveness of the proposed formulation model and solution approach. The obtained outcomes can assist to satisfy the decision-makers’ aspiration, as well as provide more alternative strategy selections based on their preferences

Financial performance prediction model based on firms’ internal capability determinants: evidence from listed firms in Thailand during the transition period of going public

AbstractThis study attempts to develop a financial performance prediction model, which explores the relationship between the internal capability determinants and the financial performance of public firms both before and after the firms participated in the Stock Exchange of Thailand (SET). The regression and logistic regression methods are employed in this model based on two internal capability determinants, namely firm financial strengths and firm characteristics. The evaluation is based on 111 listed firms that entered the SET between 2003 and 2014, inclusively. Decision makers can make use of the developed model to predict their firms’ financial performance in relative groups (high, medium and low performance groups) during the transition years when they become public. Unlike prior studies, this study includes the effect of time by considering the relative transition years (compared to the year that the firms join the stock market), which are not the calendar years. As a result, the true timing effect on the firm performance before and after going public can be discovered. The empirical evidence shows that the firms have to maintain different levels of determinants during different years of operation to yield a better financial performance. In addition, they can use the results of the prediction to prepare the most effective investment plan with the strategy of when and how much should be invested for each relative type of firms in order to upgrade its financial performance in relative to other firms in the marke [Figure: see text

Using financial incentives as a coordinating mechanism to improve the supply chain network integration

For a number of years, researchers have described and analysed the shift from traditional adversarial, 'arm's length' buyer-supplier relationships towards longer term, more cooperative relationships in which buyers and suppliers regard each other more as 'partners'. The supply chain management approach takes the view that companies do not seek to achieve profit improvements at the expense of their partners, but rather seek to make the supply network more competitive as a whole. This study tries to contribute to literature on supply chain management by explaining how to establish an incentive scheme to furnish reliable and truthful information in supply chains. This understanding can be a useful support for managers in their efforts to develop their supply networks. The results show that the coordinating policy with an incentive scheme can improve the overall channel profitability as well as the profitability of individual members in the chain beyond the traditional centralised policy. [Received 9 September 2006; Revised 13 March 2007; Accepted 18 May 2007]supply chain management; SCM; coordinating mechanisms; exchanging incentive schemes; genetic algorithms; GAs; financial incentives; supply chain integration; supply network integration.