Showing papers in "Computers & Industrial Engineering in 2017"

TL;DR: The proposed research work is focused on the design and development of a practical solution, called Sophos-MS, able to integrate augmented reality contents and intelligent tutoring systems with cutting-edge fruition technologies for operators’ support in complex man-machine interactions.

TL;DR: A competitive mathematical model of government as the leader and two competitive green and non-green supply chains as the followers is developed and for the first time, pricing policies, greening strategies and governance tariffs determining in supply chains competition under government financial intervals are discussed.

TL;DR: A hybrid model is proposed to identify the most sustainable supplier with respect to the determined attributes using an Iranian textile manufacturing company as case study and the results show that economic aspect is still the most essential aspect, followed by environmental aspect and finally social aspect.

TL;DR: A bibliometric analysis of the publications of Computers & Industrial Engineering between 1976 and 2015 is developed to identify the leading trends of the journal in terms of impact, topics, universities and countries.

TL;DR: The results prove the feasibility of the presented model and the applicability of the developed solution methodology.

TL;DR: The lack of attention paid to the correct integration of humans in Intelligent Manufacturing Systems is highlighted and solutions based on Human-Machine Cooperation principles to retain humans in the process control loop with different levels of involvement identified by the levels of automation are provided.

TL;DR: The power average operator can relieve the some influences of unreasonable data given by biased decision makers, and Heronian mean operator can consider the interrelationship of the aggregated arguments to take full advantages of these two kinds of operators.

TL;DR: Reinforcement learning with a Q-factor algorithm is used to enhance performance of the scheduling method proposed for dynamic job shop scheduling (DJSS) problem which considers random job arrivals and machine breakdowns.

TL;DR: A new method to deal with multi-criteria group decision making (MCGDM) problems with unbalanced HFLTSs by considering the psychological behavior of decision makers is developed.

TL;DR: An adopted non-dominated sorting genetic algorithm-II (NSGA-II) Meta heuristic approach is proposed to solve large instance problems and confirms that the proposed meta-heuristic is able to generate proper Pareto solutions considering all of the objectives for decision maker.

TL;DR: How the resilience of such an H-SCN system can be enhanced is demonstrated by a potential technique to share the information of the health state of firm and the knowledge of disruptions over the entire network in future if one or more firms in the network fail to function.

TL;DR: This paper investigates the pricing and service decisions of complementary products in a dual-channel supply chain which consists of two manufacturers and one common retailer and four game models are established.

TL;DR: This paper focuses on integrated production-distribution operational level scheduling problems, which explicitly take into account vehicle routing decisions of the delivery process.

TL;DR: This survey provides an overview of the existing optimization approaches to assembly line balancing and job rotation scheduling that consider physical ergonomic risks and summarizes major findings to provide helpful insights for practitioners and identify research directions.

TL;DR: The simulation results indicate that the efficient politic power on consumer demand accelerates the evolutionary path of the EV industry and a policy of dynamic taxations and static subsidies is more effective on EV industry development than other policies.

TL;DR: The proposed model investigates environmental impacts from production and transportation in a hybrid manufacturing-remanufacturing system which uses returnable transport items (RTI) for product transportation and develops best RTI management policies under the influence of these costs.

TL;DR: In this article, a new integrated model is proposed for supplier evaluation and order allocation which considers both environmental and economic factors, and a sensitivity analysis is made to examine the effect of weighting environmental criteria on total purchasing cost and quantity of order from each supplier.

TL;DR: A new multi-objective discrete virus optimization algorithm (MODVOA) with a three-part representation for each virus, an improved method for yielding the initial population, and an ensemble of operators for updating each virus is proposed to solve the MOFJSP-CPT.

TL;DR: In this study a closed-loop supply chain (CLSC) is presented, based on a case study considering the ELVs treatment in Turkey, and a linear programming (LP) model is developed to handle the reverse material flows with regard to reintegrate them into forward supply chains.

TL;DR: The results suggest that disruption, demand, and supply risks have received much attention while reputation, credit, exchange rate and information risks are least addressed.

TL;DR: A new mathematical model for the calculation of greenhouse gas emissions is developed and a new model considering fuel consumption minimization is proposed, named Green CLRP, represented by a mixed integer linear problem, which is characterized by incorporating a set of new constraints focused on maintaining the problem connectivity requirements.

TL;DR: This paper proposes a new recommendation method based on multi-criteria CF to enhance the predictive accuracy of recommender systems in tourism domain using clustering, dimensionality reduction and prediction methods, and evaluates the accuracy of recommendation method on TripAdvisior dataset.

TL;DR: Two Stackelberg game models are developed to investigate the pricing and service level decisions of a fresh agri-products supply chain consisting of one supplier, one retailer, and one third-party logistics provider and examines the impacts of channel leadership on the price and servicelevel decisions and profits.

TL;DR: A novel scheme using a Multiple Colonies Artificial Bee Colony algorithm is proposed, which aims at reducing the risk of late delivery and the potential of using real time information for data-driven vehicle scheduling.

TL;DR: It is demonstrated that in both strategies, the more generous the return policy is, the higher the demand, the selling prices and the overall profit, and that adopting a dual-channel strategy is more profitable to the supply chain.

TL;DR: It is observed from the numerical study that production disruption and TPL service have significant impacts on supply chain's performance, and the effects of buyback and revenue sharing contracts tend to emerge indifferent for relatively high probability of disruption.

TL;DR: The proposed framework can help decision makers handle the complexity that characterizes agro food supply chain design decision and that is brought on by the multi-objective nature of the problem as well as by the multiple stakeholders, thus preventing to make the decision in a segmented empirical manner.

TL;DR: This is the first study that incorporates perishability of the products into inventory routing problem with transshipment, in which the products stocked in the depot or warehouses spoil due to their nature and also environmental issues.

TL;DR: A hybrid artificial bee colony algorithm (HABC) based on Tabu search (TS) has been developed to solve the model, and a cluster grouping roulette method is proposed to better initialize the population.

TL;DR: A new two-stage compound mechanism for supplier selection based on multi-attribute auction and supply chain risk management may well improve the procurement efficiency of divisible goods and greatly reduce the procurement risk.