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Business environment is full of ups and down and this makes companies to develop different ways of using resources. By expanding life cycle of products, these ways can be cost effective and not harmful for environment. As Reverse Logistics (RL) uses a product after end of its life, it reduces pollution, therefore it has been considered as a part of sustainable development. The core goal of current research is developing a framework by which it evaluates Third Party RL Provider (3rdPRLP) using Multi-Criteria Decision-Making (MCDM) based on Fuzzy Additive Ratio ASsessment (FARAS). Thirty-seven criteria were identified, which are classified into seven main criteria. The main criteria were ranked as follows: product lifecycle position C1, RL process function C2, organizational performance C3, organizational role of RL C4, IT system and communication C5, general company consideration C6, geographical location C7. Market coverage, destination, financial considerations, integrated system, reclaim, efficiency and quality, and growth are each group’s dominant sub-criteria. In addition, the current research helps the logistics managers to better understand the key attributes’ complex relationships in the environment of decision-making. First published online 21 January 2021

Holonic multi-agent systems (HMASs) have recently attracted many researches in multi-agent systems community. Inspired from the multi-level and self-similar structures of social and biological system, holonic multi-agent systems have been widely used to model and solve complex real-world problems. The main concern in deploying HMASs is the problem of building the hierarchical holonic structure, called holarchy, and dynamically managing it during its lifetime. The way an HMAS is organized has a great impact on its applicability and performance. This paper proposes a self-organizing algorithm to build and manage the holoic structures in multi-agent systems. This algorithm is based on the local information of the agents about other agents they can communicate with. Using common social concepts, like skills, diversity, social exchange theory, and norms in definition of the algorithm, the outcomes of this research can be used in wide ranges of distributed applications. The proposed model is extensively tested in a task allocation problem; and its performance based on various design parameters is studied. Empirical results show that the proposed model properly increases the performance of the system in terms of effectiveness and efficiency.

The main goal of green supply chain management (GSCM) is to reduce the negative environmental impacts in all activities and stages of a supply chain. Evaluation of suppliers in a supply chain according to environmental criteria can help us to achieve this goal of GSCM. Since this evaluation usually comprises some alternatives and some criteria, green supplier selection (GSS) could be considered as a multi-criteria decision-making (MCDM) problem. To handle the uncertainty of information in an MCDM problem, the theory of fuzzy sets is an effective tool. Interval type-2 fuzzy sets (IT2FSs), which are characterized by an interval membership function, is very flexible to model the uncertainty of the MCDM problems. In this study, a new integrated approach based on Weighted Aggregated Sum Product Assessment (WASPAS) method, is proposed to deal with multi-criteria group decision-making problems with IT2FSs. This approach is based on the operators of IT2FSs, some modifications in the classical WASPAS method and a new procedure for calculation of criteria weights. In the procedure of calculation of criteria weights, we combine the subjective weights expressed by decision-makers with objective weights resulted from an entropy method to obtain more realistic weights. To show the applicability of the proposed approach in the real-world MCDM problems, a green supplier selection problem is used. We perform a sensitivity analysis with different weights of criteria and different values of method's parameters to show the stability of the proposed approach. This analysis shows that combining the subjective and objective weights can help to increase the stability of the proposed approach with different weights of criteria. A comparison is also made between the results of the proposed approach and some existing methods for validating the proposed approach. This analysis shows that the proposed approach is efficient and well consistent with the other methods.

There are Numerous researches in the fields of social sciences and multi-agent systems that are dedicated to studying the role of diversity vs. individual capabilities in design and performance of human and artificial societies. This paper addresses more complex multi-level structures, namely holarchies, in multi-agent systems, and conducts several analyses on the effect of individuals' behavioral diversities in the constitution and performance of the whole system. The hypothesis is that diversity directly affects the structure and performance of a holonic organization. In order to check this, we first proposed a diversity-based holonic model for multi-agent systems and then carried out a set of simulations in which a holonic multi-agent system is employed in a function optimization application. In these simulations, we manipulated the behavioral diversity of the agents in various ways and carefully observed the changes that occur on the effectiveness of the system. These observations include the quality of solutions, the height and composition of the constructed systems, and the time efficiency of the model. The empirical results show that as the diversity of intra-holon agents increases, the height of holarchy is reduced while the sizes of the holons tend to increase. On the other hand, this increase in diversity results in an increase in the performance of the system in situations that diversity of the initial population is high. However, when the diversity of the initial population is low, the diversities inside the holons need to be adjusted around 60 percent in order to boost the performance.

The increasing importance of considering environmental issues as a part of the corporate social responsibility, which has environmental and social impacts as well as affects the image and competitiveness of a firm, has encouraged companies to revise their major processes of supply chain management (SCM). Since the performance of a company heavily relies on its suppliers, it is of vital importance to incorporate environmental criteria into supplier selection problem to satisfy both conventional and environmental criteria, which have only been considered by a limited number of studies. Therefore, following a brief review of green supply chain management (GSCM) and sustainable supply chain management (SSCM) concepts and investigation of supplier selection approaches, this study after focuses on a modified Delphi method that has been applied to determine supplier selection criteria. Also, the intuitionistic fuzzy value (IFV) and interval value intuitionistic fuzzy (IVIF) have been utilised for supplier evaluation regarding the subjective nature and uncertainty of judgment. By using the Choquet Integral operator and fuzzy measures, the best supplier has been selected, and the comparison between IFV and IVIF has been made. This methodology has been applied to a manufacturing company to assess the applicability of the proposed methodology. The proposed methodology can be used for real world problems that contain fuzziness or interacting decision criteria. Moreover, due to a high level of expert involvement in the decision-making process, we claimed that the knowledge of experts has been utilised constructively.

Interaction networks, either being implicitly or explicitly specified between the agents, play a crucial role in all multi-agent systems. These structures define and limit the ways the agents should interact with their peers, and hence help to manage the coordination problems in large-scale systems. It is widely accepted that the structure of an interaction network plays a significant role in the performance of the systems. In this article, we use the interaction network of the initial agent population to construct a holonic multi-agent system. Being based on agent interaction networks, the performance of the resulting holonic multi-agent system highly depends on the structure of the underlying agent network. Here, we study this dependency in more details. The study is carried out by applying the holonification algorithm on various network topologies and assessing the constructed holonic structure in a task environment.

This paper presents a theoretical approach for a humanoid robot performing autonomously in a golf setting. The main concentration of this research is on using vision and mathematical calculations to perform and evaluate the success of each test. Most of the problems encountered in making a humanoid perform complex actions like playing golf arise from the constraints in their features and implementations. Parts of the solution comprise linear interpolation and angle calculation. Challenges faced and solved include some that will lead to a better understanding of human–robot interaction.