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The purpose of this study is to propose a conceptual framework for the exploration of appropriate lean techniques applicable to medium and large construction companies and measure their impact on the competitiveness and economic performance of construction companies in United Arab Emirates.

A questionnaire survey is conducted on 215 construction professionals in UAE to investigate the lean technique’s effect on the construction companies’ performance. The data collected were analyzed with SPSS 20.0 version software using the Cronbach’s a reliability test, correlation coefficient test and Kaiser–Meyer–Olkin test.

Analysis of lean techniques in the construction industry reveals 21 lean techniques. These techniques were categorized into the six types of lean core values. Process focus was found to be the most applied type of construction core value in the surveyed companies. This is required to focus on applying other core values as it will impact the company’s economic performance positively.

The integrity of the research findings is based on the accuracy and reliability of collected data from 215 respondents working for construction companies in UAE, implementing lean construction techniques within a their daily activates and not achieving significant project achievements in terms of quality improvement, speed and cost reduction without adopting the overall lean construction framework.

This research recommends a systematic approach for the implementation of the anticipated framework within a cyclical look-ahead period and emphasizes the practical implications of the proposed approach in the construction companies.

Research significance emphasizes increasing the effectiveness of the construction industry and influences the development of lean construction framework, which improves lean construction practices using the lean techniques. This contributes to the effort of applying lean techniques in the construction industry. Limited studies have been done in the construction industry, mainly in UAE, compared to lean manufacturing.

Considers the resource‐constrained project scheduling problem where cash inflows and outflows are tied to the occurrence of events. The objective is the maximization of the project net present value (NPV) as well as the minimization of project tardiness in the presence of a project due date. Develops hybrid scheduling rules with both NPV and tardiness considerations to enhance both objectives. Experiments extensively with a set of benchmark problems originally designed for the objective of minimizing the project duration. Demonstrates that thje hybrid rules developed here are superior in performance with respect to both objectives when compared with well known rules which are developed for the two objective of minimizing the project duration. Demonstrates that the hybrid rules developed here are superior in performance with respect to both objectives when compared with well‐known rules which are developed for the two objectives taken individually. Furthermore, the iterative algorithm improves the performance of all tested rules significantly.

This paper aims to provide an overview of principles and procedures involved in creating a faceted classification scheme for use in resource discovery in an online environment.

Facet analysis provides an established rigorous methodology for the conceptual organization of a subject field, and the structuring of an associated classification or controlled vocabulary. This paper explains how that methodology was applied to the humanities in the FATKS project, where the objective was to explore the potential of facet analytical theory for creating a controlled vocabulary for the humanities, and to establish the requirements of a faceted classification appropriate to an online environment. A detailed faceted vocabulary was developed for two areas of the humanities within a broader facet framework for the whole of knowledge. Research issues included how to create a data model which made the faceted structure explicit and machine‐readable and provided for its further development and use.

In order to support easy facet combination in indexing, and facet searching and browsing on the interface, faceted classification requires a formalized data structure and an appropriate tool for its management. The conceptual framework of a faceted system proper can be applied satisfactorily to humanities, and fully integrated within a vocabulary management system.

The procedures described in this paper are concerned only with the structuring of the classification, and do not extend to indexing, retrieval and application issues.

Many stakeholders in the domain of resource discovery consider developing their own classification system and supporting tools. The methods described in this paper may clarify the process of building a faceted classification and may provide some useful ideas with respect to the vocabulary maintenance tool.

As far as the authors are aware there is no comparable research in this area.

As the manufacturing activities in today's industries are getting more and more complex, it is required for the manufacturing firm to have a good shop floor production scheduling to plan and schedule their production orders. An accurate scheduling is essential to any manufacturing firm in order to be competitive in global market. The paper aims to discuss these issues.

Two types of shop floors, job shop and cellular layout, were developed by using WITNESS simulation package. Consequently, the performance of forward scheduling and backward scheduling in both job shop and cellular layout was compared using simulation method, and the results were analyzed by using analysis of variance (ANOVA). Through analysis, the best scheduling approach and layout to be used by manufacturing firm in order to achieve the make-to-order (MTO) production and inventory strategy were reported.

The results from simulation show that backward scheduling in job shop layout has the lowest average throughput time, lowest lateness, and highest labour productivity than forward scheduling. While in cellular layout, forward scheduling has the lowest average throughput time, lowest lateness, and highest labour productivity than backward scheduling in all conditions. It shows that the performance of scheduling approach is different in each production layout.

Suitable scheduling approach is needed in manufacturing industry as to maximize production rate and optimize machine and process capability. This paper presents an empirical study about the assembly process of radio cassette player of one manufacturing industry in order to investigate the impact of variety of orders and different number of two workers on the performance of production scheduling approach. Forward scheduling and backward scheduling are used to schedule the production orders.

The intelligence in the Internet of Things (IoT) can be embedded by analyzing the huge volumes of data generated by it in an ultralow latency environment. The computational latency incurred by the cloud-only solution can be significantly brought down by the fog computing layer, which offers a computing infrastructure to minimize the latency in service delivery and execution. For this purpose, a task scheduling policy based on reinforcement learning (RL) is developed that can achieve the optimal resource utilization as well as minimum time to execute tasks and significantly reduce the communication costs during distributed execution.

To realize this, the authors proposed a two-level neural network (NN)-based task scheduling system, where the first-level NN (feed-forward neural network/convolutional neural network [FFNN/CNN]) determines whether the data stream could be analyzed (executed) in the resource-constrained environment (edge/fog) or be directly forwarded to the cloud. The second-level NN ( RL module) schedules all the tasks sent by level 1 NN to fog layer, among the available fog devices. This real-time task assignment policy is used to minimize the total computational latency (makespan) as well as communication costs.

Experimental results indicated that the RL technique works better than the computationally infeasible greedy approach for task scheduling and the combination of RL and task clustering algorithm reduces the communication costs significantly.

The proposed algorithm fundamentally solves the problem of task scheduling in real-time fog-based IoT with best resource utilization, minimum makespan and minimum communication cost between the tasks.

This study develops a model and algorithm to solve the decentralized resource-constrained multi-project scheduling problem (DRCMPSP) and provides a suitable priority rule (PR) for coordinating global resource conflicts among multiple projects.

This study addresses the DRCMPSP, which respects the information privacy requirements of project agents; that is, there is no single manager centrally in charge of generating multi-project scheduling. Accordingly, a three-stage model was proposed for the decentralized management of multiple projects. To solve this model, a three-stage solution approach with a repeated negotiation mechanism was proposed.

The experimental results obtained using the Multi-Project Scheduling Problem LIBrary confirm that our approach outperforms existing methods, regardless of the average utilization factor (AUF). Comparative analysis revealed that delaying activities in the lower project makespan produces a lower average project delay. Furthermore, the new PR LMS performed better in problem subsets with AUF < 1 and large-scale subsets with AUF > 1.

A solution approach with a repeated-negotiation mechanism suitable for the DRCMPSP and a new PR for coordinating global resource allocation are proposed.

This study aims to propose a new genetic algorithm for solving supply chain scheduling and routing problem in a multi-site manufacturing system. The main research question is: How is the production and transportation scheduled in a multi-site manufacturer? Also the sub-questions are: How is the order assigned to the suppliers? What is the production sequence of the assigned orders to a supplier? How is the order assignment to the vehicles? What are the vehicles routes to convey the orders from the suppliers to the manufacturing centers? The authors’ contributions in this paper are: integration of production scheduling and vehicle routing in multi-site manufacturing supply chain and proposing a new genetic algorithm inspired from the role model concept in sociology.

Considering shared transportation system in production scheduling of a multi-site manufacturer is investigated in this paper. Initially, a mathematical model for the problem is presented. Afterwards, a new genetic algorithm based on the reference group concept in sociology, named Reference Group Genetic Algorithm (RGGA) is introduced for solving the problem. The comparison between RGGA and a developed algorithm of literature closest problem, demonstrates a better performance of RGGA. This comparison is drawn based on many test problems. Moreover, the superiority of RGGA is certificated by comparing it to the optimum solution in the small size problems. Finally, the authors use real data collected from a drug manufacturer in Iran to test the performance of the algorithm. The results show the better performance of RGGA in comparison with obtained outputs from the real case.

The authors presented the mathematical model of the problem and introduced a new genetic algorithm based on the “reference group” concept in sociology. Robert K. Merton is a sociologist who presented the concept of reference groups in society. He believed that some people in each society such as heroes or entertainment artists affect other people. The proposed algorithm uses the reference group concept to the genetic algorithm, namely, RGGA. The comparison of the proposed algorithm with DGA and the optimum solution shows the superiority of RGGA. Finally, the authors implement the algorithm in a real case of drug manufacturing and the results show that the authors’ algorithm gives better outputs than obtained outputs from the real case.

One of the major objectives of supply chains is to create a competitive advantage for the final product. This intension is only achieved when each and every element of the supply chain considers customers’ needs in every function of theirs. This paper studies scheduling in the supply chain of a multi-site manufacturing system. It is assumed that some suppliers produce raw material or initial parts and convey them by a fleet of vehicles to a multi-site manufacturer.

In a quest to meet increasing pressure to incorporate environmental and sustainability factors due to the legislations and growing public awareness, companies are rethinking of strategizing their supply chain network to take control of the reverse flow of products as well. This growing interest has also led to tremendous growth in publications occurring in several reputed journals in the last few years. In this context, the purpose of this article is to perform a systematic literature survey of recent and state-of-the-art papers in order to draw insights and highlight the future directions.

This paper has selected and reviewed 204 papers published from the year 2002–2017. The papers were collected from the web of science and Google scholar database which have the DOI number. The selected papers were then categorized into main five core areas of RSC management namely reverse supply chain (RSC), Reverse Logistics (RL), Remanufacturing, Closed-Loop Supply Chain (CLSC) and Product Recovery Systems (PRS) and then analyzed with great detail. Finally, the research gaps that were identified from the study have been highlighted for future research opportunities.

This paper would serve as a roadmap to the managers who wish to align their forward and reverse supply chains for overall growth and development. It provides an in-depth knowledge on RSC to the researchers working in this domain. The scholars would be able to identify the areas of RSC which have been already addressed and the areas which remain unaddressed.

This paper presents a systematic literature survey of state-of-the-art papers that was published in the reputed journal in the area of RSC. Total 204 numbers of papers which were published in the reputed journals between 2002 and 2017 are reviewed, categorized and analysed to draw the opportunities and future research direction in the area of RSC.

Many organizations are analysing the feasibility of using Japanese production methods and concepts. Examines how allowing individuals discretion in selecting among various production scheduling techniques, combined with real‐time feedback, affects their job‐scheduling performance. The results of the experiments involving sequencing jobs through work centres, illustrate that when discretion was afforded, performance improved. This result suggests that providing employees with discretionary leeway and real‐time feedback enables them to improve the production system continuously.

The purpose of this paper is to propose a structured model for evaluating and selecting the best third party reverse logistics provider (3PRLP) under fuzzy environment for the battery industry.

In this paper, the multi‐criteria decision‐making tools such as analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (FAHP) are adopted to solve the problem of selection of 3PRLP.

In a real‐time situation, collecting the returned products from the customer end to the manufacturer end becomes more tedious, time consuming work and also it makes the information flow in the supply chain management more complex. A separate logistics system has to be developed in order to inspect and maintain the collected returned products in the down stream management. This current scenario encourages the top‐level management to seek for an alternative for collecting the returned products instead of making their supply chain structure to be complex. This gives rise to the term called 3PRLP. The 3PRLP will collect the returned products, inspect them and categorize them according to the various reverse logistics operations. A key finding of this work is a model to determine the best 3PRLP for the battery industry.

This work provides a useful decision model for practicing managers and researchers within this area, and also shows the various relationships, and processes the information required for the management involved in the selection of a reverse logistics provider under fuzzy environment.

In this research, seven attributes and 34 sub‐attributes are considered and an interpretation of reverse logistics attributes in terms of their pair‐wise comparisons has been carried out. Attributes possessing lower priorities in the AHP and FAHP need to be taken care on a selection of best 3PRLP.