Showing papers in "Computers & Industrial Engineering in 2013"

TL;DR: This paper focuses on reviewing the most recent advances in HLP from 2007 up to now, and a review of all variants of HLPs (i.e., network, continuous, and discrete HLPs) is provided.

TL;DR: In this paper, an improved cuckoo search algorithm is presented, enhancing the accuracy and convergence rate of the cuckoff search algorithm, and the performance of the proposed algorithm is tested on some complex engineering optimization problems.

TL;DR: The proposed heuristic solution approach based on particle swarm optimization (PSO) in which a local search is performed by variable neighborhood descent algorithm (VND) implements an annealing-like strategy to preserve the swarm diversity.

TL;DR: This paper considers the multi-objective reliability redundancy allocation problem of a series system where the reliability of the system and the corresponding designing cost are considered as two different objectives and a fuzzy multi- objective optimization problem (FMOOP) is formulated from the original crisp optimization problem.

TL;DR: A heuristic method for efficiently finding near-optimal solutions for bicycle sharing systems incorporating bicycle stock considerations is proposed and a numerical example is created to illustrate the model and proposed solution algorithm.

TL;DR: This paper reviews the typical complexity drivers that are faced in different types of supply chains and presents the complexity driver and solution strategy pairings, in the form of a matrix to assist decision-makers in formulating appropriate strategies to deal with complexity in their supply chains.

TL;DR: In this article, a critical overview of the existing international literature on simulation models for emergency medical services (EMS) by pinpointing the issues considered, the associated modeling assumptions as well as the results obtained.

TL;DR: The results showed that the method was able not only to detect the failure in an incipient stage but also to identify the location of the defect and qualitatively assess its evolution over time.

TL;DR: A recently developed meta-heuristic optimization algorithm cuckoo search is hybridized with well-known genetic algorithm (GA) called CS-GA is proposed to solve the reliability and redundancy allocation problem.

TL;DR: This paper presents how metaheuristics can be used in order to minimize the total tardiness for a given set of customer orders, and proposes two heuristics based on Iterated Local Search and Attribute-Based Hill Climber, both based on a simple tabu search principle.

TL;DR: A modified failure mode and effects analysis method to select new suppliers from the supply chain risk's perspective and applies the analytic hierarchy process (AHP) method to determine the weight of each criterion and sub-criterion for supplier selection shows that the case company can categorize its suppliers more effectively and at the same time select a low-risk supply chain partner.

TL;DR: A mathematical formulation that combines an integer programming model representing location and dispatching decisions, with a hypercube model representing the queuing elements and congestion phenomena is developed, concluding that the joint approach can give insights of the implicit trade-offs between several conflicting optimization criteria.

TL;DR: MORPGEASA, a Pareto-based hybrid algorithm that combines evolutionary computation and simulated annealing, is proposed and analyzed for solving these multi-objective formulations of the VRPTW and the results obtained show the good performance of this hybrid approach.

TL;DR: A formal formulation, two heuristic algorithms are proposed, and a particle swarm optimization (PSO) algorithm is developed to effectively tackle a scheduling problem in a multiple-machine system where the computing speeds of the machines are allowed to be adjusted during the course of execution.

TL;DR: Computational results show that GA can be considered as an effective and efficient solution algorithm for solving stochastic DLBP with station paralleling in terms of the solution quality and CPU time.

TL;DR: An adapted version of the non- dominated sorting genetic algorithm (NSGA-II) is proposed to solve the problem of reconfigured manufacturing systems (RMSs) design based on products specifications and reconfigurable machines capabilities.

TL;DR: A recovery model is explored for a two-stage production and inventory system with the possibility of transportation disruption, showing that the optimal recovery schedule is highly dependent on the relationship between the backorder cost and the lost sales cost parameters.

TL;DR: This paper proposes an allocation mechanism that is based on a common dual weights approach that can be interpreted as providing equal endogenous valuations of the inputs and outputs in the reference set and claims that this approach assures a consistent and equitable internal allocation.

TL;DR: The results show that both IT alignment and information sharing have direct and positive effects on operational performance, and Chinese managers may have different emphases on IT resource/information sharing capability deployment for operational efficiency and effectiveness.

TL;DR: This research deals with line balancing under uncertainty and presents two robust optimization models that are protected against this type of disruptions and should serve as the basis for a decision support system on this subject.

TL;DR: The results suggest that the inclusion of three way recovery in reverse channel and product exchange policy in the forward channel reduce the order variation and bullwhip effect at both retailer and distributor level and increases the profitability of RL operations.

TL;DR: A method based on prospect theory is proposed to solve the multiple attribute decision making (MADM) problem considering aspiration-levels of attributes, where attribute values and aspiration- levels are represented in two different formats: crisp numbers and interval numbers.

TL;DR: A consensus-based approach for effectively solving the multicriteria group decision making problem is presented and the subjectiveness and imprecision of the decision making process is adequately handled by using intuitionistic fuzzy numbers.

TL;DR: The proposed NEBM model combines the radial and non-radial measures of efficiency into a unified framework for solving network DEA problems and is presented to exhibit the efficacy of the procedures and to demonstrate the applicability of the proposed method to a supply chain performance evaluation problem in the semiconductor industry.

TL;DR: This paper proposes hybrid differential evolution (HDE) algorithms for solving the flexible job shop scheduling problem (FJSP) with the criterion to minimize the makespan and a local search algorithm based on the critical path is embedded in the DE framework to balance the exploration and exploitation by enhancing the local searching ability.

TL;DR: A routing method to control the picker congestion that challenges the traditional assumption regarding the narrow-aisle order picking system and achieves the shortest total picking time in most instances and performs well in dealing with the congestion.

TL;DR: This research deals with balancing a mixed-model U-line in a Just-In-Time (JIT) production system to reduce the number of stations via balancing the workload and maximizing the weighted efficiency.

TL;DR: It is found that channel acceptance plays a critical role in influencing equilibrium prices and profits in the dual-channel distribution system and both the supplier and the retailer are worse off in the Nash game.

TL;DR: A mathematical model is developed that investigates the impact of learning and forgetting of a heterogeneous workforce on order picking time and, consequently, on storage assignment decisions and shows thatlearning and forgetting should be considered in order to achieve a proper planning of storage assignment strategies.

TL;DR: Numerical experiments show that the multi-scenario solutions provide a hedge against uncertainty when compared to deterministic decisions and exhibit some forms of robustness, which mitigate the risks of not meeting empty container demand.