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The present paper describes a Fortran library FLIPP constituting a run‐time environment that is linked to scientific applications software (such as finite‐element analysis programs) to support programming of interactive program control and use of persistent user‐defined dynamic data structures. The system consists of control and data definition and manipulation subsystems. The FLIPP routines are fully‐portable standard Fortran 77 procedures and the use of FLIPP leads the programmer to information hiding, e.g. as in object‐oriented systems. Program design and maintenance are facilitated to a considerable degree, while at the same time the performance of the programs using the FLIPP system remains fairly good as demonstrated by the examples.

The purpose of this paper is to propose a method for solving multi-objective linear programming (MOLP) with interval coefficients using positioned programming and interactive fuzzy programming approaches.

In the proposed algorithm, first, lower and upper bounds of each objective function in its feasible region will be determined. Afterwards using fuzzy approach, considering a membership function for each objective function and finally using grey linear programming, the solution for this problem will be obtained.

According to the presented example, in this paper, the proposed method is both simple in use and suitable for solving different problems. In the numerical example mentioned in this paper, the proposed method provides an acceptable solution for such problems.

As in most real-world situations, the coefficients of decision models are not known and exact. In this paper, the authors consider the model of MOLP with interval data, since one of the solutions to cover uncertainty is using interval theory.

Based on using grey theory and interactive fuzzy programming approaches, an appropriate method has been presented for solving MOLP problems with interval coefficients. The proposed method, against the complex methods, has less effort and offers acceptable solutions.

This paper presents an interactive fuzzy satisfying method by assuming that the decision maker (DM) has fuzzy goals for each of the objective functions in multiobjective nonlinear programming problems. The fuzzy goals of the DM are quantified by eliciting the corresponding membership functions through the interaction with the DM. After determining the membership functions for each of the objective functions, in order to generate a candidate for the satisficing solution which is also a Pareto optimal, the DM selects an appropriate standing membership function and specifies his/her aspiration levels of achievement of the other membership functions, called constraint membership values. For the DM's constraint membership values, the corresponding constraint problem is solved and the DM is supplied with the Pareto optima] solution together with the trade‐off rates between a standing membership function and each of the other membership functions. Then by considering the current values of the membership functions as well as the trade‐off rates, the DM acts on this solution by updating his/her constraint membership values. In this way, the satisficing solution for the DM can be derived efficiently from among a Pareto optimal solution set by updating his/her constraint membership values. On the basis of the proposed method, a time‐sharing computer program is written and an application to regional planning is demonstrated along with the corresponding computer outputs.

Logistics is the part of the supply chain (SC) that plans, executes and handles forward and reverse movement and storage of products, services and related information, in order to respond to customers' needs effectively and efficiently. The main concern for logistics is to ensure that the correct product is placed at the right time. This paper introduces a linear model of shipping focused on decision-making, which includes configuration of shipping network, choosing of transport means and transfer of individual customer shipments through a particular transport system.

In this study, authors try to address the problem of supply chain network (SCN) where the primary goal is to determine the appropriate order allocation of products from different sources to different destinations. They also seek to minimize total transportation cost and inventory cost by simultaneously determining optimal locations, flows and shipment composition. The formulated problem of getting optimal allocation turns out to be a problem of multi-objective programming, and it is solved by using the max-addition fuzzy goal programming approach, for obtaining optimal order allocation of products. Furthermore, the problem demand and supply parameters have been considered random in nature, and the maximum likelihood estimation approach has been used to assess the unknown probabilistic distribution parameters with a specified probability level (SPL).

A case study has also been applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. Results of this study are very relevant for the manufacturing sector in particular, for those facing logistics issues in SCN. It enables researchers and managers to cope with various types of uncertainty and logistics risks associated with SCN.

The principal contribution of the proposed model is the improved modelling of transportation and inventory, which are affected by different characteristics of SCN. To demonstrate computational information of the suggested methods and proposed model, a case illustration of SCN is provided. Also, environmentalism is increasingly becoming a significant global concern. Hence, the concept proposed could be extended to include environmental aspects as an objective function or constraint.

Efficient integration of logistical cost components, such as transportation costs, inventory costs, with mathematical programming models is an important open issue in logistics optimization. This study expands conventional facility location models to incorporate a range of logistic system elements such as transportation cost and different types of inventory cost, in a multi-product, multi-site network. The research is original and is focused on case studies of real life.

To be successful, pervasive computing requires a balance of computing, design, and business requirements to be considered throughout the design process. Achieving this synthesis requires a level of interdisciplinary design that is not present in current pervasive design tools. To understand the state of the art and provide insight to future tool designers, the purpose of this paper is to present a survey of design tools for pervasive computing and consider their ability to be used in interdisciplinary design.

The authors have performed a survey of tools covering many areas within pervasive computing and have evaluated the abilities of each tool with established metrics for pervasive design tools.

While the paper has found many design tools are available for constructive pervasive applications, few are suitable through all phases of the design cycle or useful across all the intended application domains of pervasive computing.

This survey provides an understanding of the state of pervasive design tools, with regards to interdisciplinary design, which has not previously been performed. Additionally, the authors provide evaluations of the pervasive tools when used in an interdisciplinary setting. These evaluations provide insight to key metrics and allow tool designers to understand the needs of their intended audience.

The current goal is to implement a description grammar that generates housing briefs based on user and site data. The ultimate goal is to customize mass housing. This paper discusses these issues. Previous research proposed a mathematical model for the automatic generation of customized designs based on description and shape grammars. This paper describes the implementation of a description grammar that codifies the Portuguese housing design guidelines, as well as the intelligence of a human designer using them inferred after experimental work. Knowledge was sequentially converted from table format into English, Mathematical notation, and then the CLIPS language. Java Experts system Shell is the rule application engine, and JAVA and XML are used for coding theinterface and information tables, respectively.It describes how to implement a description grammar and it shows the feasibility of using them for automating the generation of housing briefs that contain enough technical information for design. In a subsequent step, it permits the automatic generation of housing solutions in real time. Backtracking is limited, theinterface does not provide visual clues for improving understanding of the available options, and the brief does not record intuitive or emotional information. It can help designers identifying the specifications of their clients' houses. It can be linked to a system that automatically generates, in a given language, housing solutions that match such specifications, thereby enabling the mass customization of housing. This paper describes the first practical implementation of a description grammar found in the literature.

What Is “Interactive Video”? Interactive video is a phrase which is suddenly cropping up all over the place, in journals, at seminars, in the popular press. But what does it mean? And what does it mean to you? Is it just another buzz‐phrase? Or is it a term which is soon going to enter our training vocabulary? Well, I think it is a revolutionary new medium — and in the course of this article, I mean to convince you of my belief.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

Seeks to explores the idea of career‐focused, vocational higher education and give an overview of the current offerings of degrees, programs and majors that focus on games, simulations and interactive media.

Provides an overview of educational courses supplied by various institutions which are capitalising on student and industry demand by offering officially accredited degrees in the study of games.

Students benefit most from the developing educational trend, and it makes economic sense for institutions to update their offerings to allow pedagogy to improve as the concept of what is involved in higher education expands.

Explores specifically how institutions are capitalizing on student and industry demand by offering officially accredited degrees in the study of games.

The purpose of this paper is to explore and emphasize the impact of academic computer game studies programs on library services and collections.

A review of the literature related to the relationship between gamers, game studies, and libraries, precedes discussion of the background of academic computer game studies programs. The potential challenges and opportunities concerning collection development, information literacy instruction, and reference within academic libraries are addressed along with highlights of emerging best practices.

The paper provides analysis of game studies as an emerging academic discipline and of the scholarly communication within this field. It also highlights emerging practices within academic librarians serving students and faculty in this field.

Because game studies is a new discipline, best practices to meet users' needs are just beginning to be established for academic libraries. Further research is needed in the area of information‐seeking behavior, perception of game studies' students and faculty, and their information literacy skills.

This is an opportunity for librarians who serve students and faculty in game studies to learn about the history of this discipline and what several academic librarians are currently doing to meet their needs in collection development, information literacy instruction, and reference services.

While discussing the history of game studies as an academic program, the paper also highlights the issues related to library services and collections for the emerging academic discipline of game studies in an effort to support academic librarians who work with game studies students and faculty.