A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality

Managing service quality is vital to retain customer satisfaction and augment revenues for any business organization. Often it is difficult to assess service quality due to lack of quantifiable measures and limited data. In this paper, we present a hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating service quality of urban transportation systems. The proposed approach consists of three steps. The first step involves development of a SERVQUAL based questionnaire to collect data for measuring transportation service quality. The participants provide linguistic assessments to rate the service quality criteria and the alternatives. In step 2, the linguistic ratings are combined through fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen. In step 3, sensitivity analysis is conducted to evaluate the influence of criteria weights on the decision making process.The strength of the proposed approach is its practical applicability and ability to provide solution under partial or lack of quantitative information. An application of the proposed approach for evaluation of service quality of metro in Montreal is provided.     

Analytical Modeling of a Triple Material Double Gate TFET with Hetero-Dielectric Gate Stack

Silicon - In this paper, we propose and develop an analytical model of a Triple material double gate Tunnel Field Effect Transistor (TM-DG TFET) with hetero-dielectric gate oxide stack comprising...     

Strategic capacity planning in supply chain design for a new market opportunity

This paper addresses the problem of supply chain design at the strategic level when production/distribution of a new market opportunity has to be launched in an existing supply chain. The new market opportunity is characterized by a deterministic forecast expected to occur per period. The product (or service) is assumed to be produced (or provided) in a three-stage capacitated supply chain where the first stage concerns suppliers, the second stage producers and the final stage customers. There could be multiple alternatives at each stage which are defined as nodes. Nodes in each stage are connected to the next stage through capacitated transportation systems. Production capacity at the second stage (i.e. producers) are also limited since they may already be involved in other existing activities. The objective is to perform strategic capacity planning in the supply chain in order to meet the demand of the new opportunity at minimal cost. A linear running cost is associated with each node. If the decision is to increase the capacity of a node, then a fixed cost applies, followed by a cost that is proportional to the additional capacity.

The overall problem can be modelled as a large-scale mixed integer linear programming problem. A solution algorithm is developed to overcome difficulties associated with the size of the problem and is tested on empirical data sets. The overall contribution is an analytical tool that can be employed by managers responding to the new market opportunity at the strategic level for supply chain design.     

Mitigating supply disruption with a backup supplier under uncertain demand: competition vs. cooperation

In case of supply disruption following major disasters, many supply chains tend to break down due to stock-outs and take a long time to recover. However, by keeping emergency sources of supply, some supply chains continue to function smoothly even after a major disaster. In this work, using a game-theoretic-framework, we consider a two-suppliers-one-retailer supply chain with price-dependent stochastic demand in which suppliers are prone to disruption. To investigate the impact of supply disruption we consider two models: SC model, in which the retailer does not maintain any emergency sources of supply against any supply disruption, and SCB model, in which the retailer maintains a backup supplier to mitigate the impact of supply disruption. We mainly focus on the pricing strategies of the suppliers and the mitigating strategies of the retailer under supply and demand uncertainty. We address two coordinating mechanisms to enhance supply chain performance. Our results indicate that in the presence of supply disruption, even with lower probabilities, the retailer would always prefer to take the advantage of a backup supplier and the optimal reserve quantity increases with disruption probabilities. We further investigate the scenario in which the suppliers would always prefer to cooperate with each other.     

A dynamic programming approach to GA-based heuristic for multi-period CF problems

In this paper we have introduced a multi-period cell formation (CF) model which is more computationally challenging than the most comprehensive CF models in the literature. A dynamic programming (DP) based approach coupled with GA-based heuristic is proposed to solve the multi-period problem. Since, the introduced dynamic programming is general and can be applied to any GA-based heuristic with full rejuvenation cycles to solve the multi-period part of the model, we focused only on the DP approach in this paper but have explained the interface with the GA-based heuristic. Illustrative example has been provided that clarifies the application of DP-heuristic. The performance of the DP-heuristic has been evaluated against LINGO and multi period GA-based heuristic.     

A column generation based heuristic for the capacitated vehicle routing problem with three-dimensional loading constraints

This paper addresses an integrated problem of vehicle routing and three-dimensional loading with additional practical constraints such as stability, fragility and LIFO. A column generation (CG) technique-based heuristic is proposed to handle this problem. To generate new columns in CG technique, first, an elementary shortest path problem is solved to find routes with negative reduced cost. Then an extreme point-based heuristic method is employed to verify feasibility of obtained routes in terms of loading and other constraints. To speed up the CG technique, fast column generation is also performed by applying an efficient heuristic pricing method. The CG technique, tested on the benchmark instances, outperforms the efficient tabu search method developed in the literature in terms of solution quality and computation time.     

Room-temperature equal channel angular extrusion of pure magnesium

In this paper, we demonstrate a way to impart severe plastic deformation to magnesium at room temperature to produce ultrafine grain size of ～250 nm through equal channel angular extrusion (ECAE). The strategy to deform magnesium at lower temperature or to achieve such grain sizes has been proposed as: (i) to obtain a suitable initial orientation with high Schmid factor for basal slip and low Schmid factor for pyramidal/prismatic slip; (ii) to take advantage of low stacking fault energy of basal and high stacking fault energies of prismatic/pyramidal planes in order to relatively work-harden the basal plane with respect to the pyramidal/prismatic plane; and (iii) to lower the temperature of deformation in steps, leading to continual refinement of grains, resulting in finer grain size. The experimental as well as simulated texture of ECAE-processed samples indicate that the deformation mechanism leading to ultrafine grain size is slip-dominated. The recrystallization mechanism during ECAE has been found to be orientation-dependent.     

Application of fuzzy TOPSIS in evaluating sustainable transportation systems

Sustainable transportation systems are the need of modern times. There has been an unexpected growth in the number of transportation activities over years and the trend is expected to continue in the coming years. This has obviously associated environmental costs like air pollution, noise, etc. which is degrading the quality of life in modern cities. To cope us this crisis, municipal administrations are investing in sustainable transportation systems that are not only efficient, robust and economical but also friendly towards environment. The challenge before the transportation decision makers is how to evaluate and select such sustainable transportation systems. In this paper, we present a multicriteria decision making approach for selecting sustainability transportation systems under partial or incomplete information (uncertainty). The proposed approach comprises of three steps. In step 1, we identify the criteria for sustainability assessment of transportation. In step 2, experts provide linguistic ratings to the potential alternatives against the selected criteria. Fuzzy TOPSIS is used to generate aggregate scores for sustainability assessment and selection of best alternative. In step 3, sensitivity analysis is performed to determine the influence of criteria weights on the decision making process. A numerical illustration is provided to demonstrate the applicability of the approach.The strength of the proposed work is its practical applicability and the ability to generate good quality solutions under uncertainty.