Abstracts:In this paper, one of the most common layout design approaches in general factory design – minimum flow-weighted distance (min-distance) layout – is verified for semiconductor fabrication facility (FAB) design. In min-distance layout design, machines or workstations with high flow rates are allocated close to each other to minimize the total distance of the material flow. This approach is widely used in various industries including semiconductor manufacturing. However, some research also discusses the drawbacks of this approach due to flow congestions and heavy traffic in material handling systems. We validate the min-distance approach with actual data from a modern 300-mm DRAM FAB. We logically generate 18 different cases with different layouts, overhead hoist transport track configurations, and production scenarios. The effectiveness and drawbacks of the min-distance approach in FAB design is investigated with these cases. From the simulation analysis using the Design of Experiments method, we logically show that the performance of material delivery is sensitive to the production volume in the min-distance layout. Also, the performance of the min-distance layout is significantly degraded when the volume is heavy; however, performance can be improved considerably with a few modifications to the bays. We also provide practical tips for an effective layout design method from the insight gained from the simulation analysis. This paper contributes to the critical analysis of the conventional layout design method and the identification of its effectiveness and limitations by using actual FAB data.

Abstracts:In this paper, we propose a decentralized approach to solve multiple-criteria single machine scheduling problems. We consider a single machine that is utilized by two agents where each of them has its own jobs and a private objective. The objective function of the first agent is the total completion time or the total weighted completion time of its jobs, respectively, whereas the objective function of the second agent is the maximum lateness or the total weighted completion time of its jobs. The problem is motivated by scheduling problems found in semiconductor manufacturing. An automated negotiation mechanism is presented to solve the scheduling problems. The basic ingredient of the mechanism is a mediator that proposes contracts using a variable neighborhood search (VNS) technique. We study the behavior of both greedy and cooperative agents. In addition, a hybrid strategy is developed where the mediator accepts deteriorations of the objective values with a certain probability. The performance of the negotiation schemes is assessed using randomly generated problem instances. It turns out that the solutions determined by the negotiation mechanism are close to the Pareto frontier from a centralized approach with full information. We use a problem-specific Non-Dominated Sorting Genetic Algorithm (NSGA)-II scheme to determine the solutions on the Pareto frontier. It is shown that the degree of cooperation of the two agents depends on the objective function used.

Abstracts:Over the past decades, the Vehicle Routing Problem (VRP) and its variants have grown ever more popular in the academic literature. Yet, the problem characteristics and assumptions vary widely and few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the VRP literature published between 2009 and June 2015. Based on an adapted version of an existing comprehensive taxonomy, we classify 277 articles and analyze the trends in the VRP literature. This classification is the first to categorize the articles to this level of detail.

Abstracts:In this paper, a likelihood-based TODIM approach based on multi-hesitant fuzzy linguistic information is developed for the selection and evaluation of contractors in logistics outsourcing. First, various definitions and operations related to hesitant fuzzy linguistic term sets (HFLTSs) and hesitant fuzzy linguistic sets (HFLSs) are discussed. Next, the definition of multi-hesitant linguistic term sets (MHFLTSs) is reviewed, which can eliminate the limitations associated with HFLTSs and HFLSs as well as emphasize the significance of repeated values. Then, a likelihood function is developed for multi-hesitant fuzzy linguistic term elements (MHFLTEs) based on a generalized function of the possibility degree of real numbers. Using this generalized function based on linguistic scale functions, alternatives that satisfy certain properties can be selected according to various semantic situations and the preferences of decision makers. Finally, the likelihood function of MHFLTEs is embedded into TODIM to address decision-making problems in which decision makers exhibit bounded rationality, and hesitance and repetitiveness exist in the linguistic evaluation information. According to the results of the illustrative examples and comparative analysis, the proposed approach can be used to effectively solve multi-criteria decision making problems involving the selection and evaluation of third-party logistics service providers.

Abstracts:Knapsack Problems with Setups (KPS) have received increasing attention in recent research for their potential use in the modeling of various concrete industrial and financial problems, such as order acceptance and production scheduling. The KPS problem consists in selecting appropriate items, from a set of disjoint families of items, to enter a knapsack while maximizing its value. An individual item can be selected only if a setup is incurred for the family to which it belongs. In this paper, we propose a tree search heuristic to the KPS that generates compound moves by a strategically truncated form of tree search. We adopt a new avoid duplication technique that consists in converting a KPS solution to an integer index. The efficiency of the proposed method is evaluated by computational experiments involving a set of randomly generated instances. The results demonstrate the impact of the avoiding duplication technique in terms of enhancing solution quality and computation time. The efficiency of the proposed method was confirmed by its ability to produce optimal and near optimal solutions in a short computation time.

Abstracts:Air traffic in Europe is predicted to increase considerably over the next decades. In this context, we present a study of the interactions between the costs due to ground-holding regulations and the costs due to en-route air traffic control. We dulator that considers the regulation delays, aircraft trajectories, and air conflict resolution. Through intensive simulations based on traffic forecasts extrapolated from French traffic data for 2012, we compute the regulation delays and avoidance maneuvers according to two scenarios: the current regulations and no regulations. The resulting cost analysis highlights the exponential growth in regulation costs that can be expected if the procedures and the airspace capacity do not change. Compared to the delay costs, the costs of the air traffic control are negligible with or without regulation. The analysis reveals the heavy controller workloads when there are no regulations, suggesting the need for regulations that are appropriate for large traffic volumes and an improved ATC system. These observations motivate the design of a third scenario that computes the sector capacities to find a compromise between the increase in the delay costs due to ground-holding regulations and the increase in the controller workload. The results reveal the sensitivity of the delay costs to the sector capacity; this information will be useful for further research into ATM sector capacity and ATC automated tool design. Finally, because of the growing interest in the free flight paradigm, we also perform a traffic and cost analysis for aircraft following direct routes. The results obtained highlight the fuel and time savings and the spatial restrictions that companies use to avoid congested areas.

Abstracts:The fixed charge network flow (FCNF) problem is a classical NP-hard combinatorial problem with wide spread applications. To the best of our knowledge, this is the first paper that employs a statistical learning technique to analyze and quantify the effect of various network characteristics relating to the optimal solution of the FCNF problem. In particular, we create a probabilistic classifier based on 18 network related variables to produce a quantitative measure that an arc in the network will have a non-zero flow in an optimal solution. The predictive model achieves 85% cross-validated accuracy. An application employing the predictive model is presented from the perspective of identifying critical network components based on the likelihood of an arc being used in an optimal solution.

Abstracts:This paper presents Taguchi method coupled with fuzzy logic for dealing with multi-objective optimisation problems for dynamic scheduling in robotic flexible assembly cells (RFACs). This is the first study to address these particular problems. In this study, Taguchi optimisation method has been applied to reduce the number of experiments required for scheduling RFACs. The experiments are implemented with four different scheduling factors, namely sequencing rule, dispatching rule, cell utilisation and due date tightness. These factors are difficult to optimise considering the objectives of multiple functions instead of a single objective. Therefore, a multiple performance characteristics index (MPCI) based fuzzy logic approach has been developed to derive the optimal solution. The predicted results of MPCIs have been verified via a confirmation test. Results of the confirmation test show significant improvement in MPCI using the optimal levels of the scheduling factors.

Abstracts:Computer-based manufacturing scheduling tools can play a key role in the management of industrial operations, as obtaining economic and reliable schedules is at the core of excellence in customer service and of efficiency in manufacturing companies. As a consequence, this topic has been receiving an increasing interest in the last decades, resulting in a number of case studies and descriptions of implementation of these tools. However, to the best of our knowledge, there is no review of these cases in order to classify existing references and to identify relevant issues still not properly addressed. Therefore, in this paper we carry out a systematic review of case studies of manufacturing scheduling tools. In order to provide a coherent taxonomy for the analysis of these tools, we develop a classification based on the functionalities of the manufacturing scheduling tools. Using this framework, existing contributions are classified and discussed, and a number of conclusions and open issues are identified. We hope that our work can establish a coherent picture of the topic so it serves as a starting point for future research.