Assessing service satisfaction between a 3PL provider and a vehicle manufacturer using the SERVQUAL technique

This paper reports on a new study conducted within a leading UK based (and US owned) car manufacturing company looking at the satisfaction between parties within a newly formed third party logistics (3PL) relationship. The study contains a two-way assessment of the relationship (i.e. the vehicle manufacturer’s Parts Supply and Logistics Operation’s assessment of the 3PL’s service and the 3PL’s assessment of the vehicle manufacturer’s relationship management ability). The study principally used an online SERVQUAL survey, (backed up with an on-line questionnaire, and face to face interviews) for data collection. The paper discusses the background and problems that have arisen in the relationship, the analysis of how each of the parties sees one other in terms of the service provided. Also, the findings and recommendations presented to management are outlined: these include factors such as the need for information sharing, reliability, flexibility, role specificity, trust and effective requirements management.

Premium e-grocery:exploring value in logistics integrated service solutions

E-grocery is gradually becoming viable or a necessity for many families. Yet, most e-supermarkets are seen as providers of low value "staple" and bulky goods mainly. While each store has a large number of SKU available, these products are mainly necessity goods with low marginal value for hedonistic consumption. A need to acquire diverse products (e.g., organic), premium priced products (e.g., wine) for special occasions (e.g., anniversary, birthday), or products just for health related reasons (e.g., allergies, diabetes) are yet to be served via one-stop e-tailers. In this paper, we design a mathematical model that takes into account consumers' geo-demographics and multi-product sourcing capacity for creating critical mass and profit. Our mathematical model is a variant of Capacitated Vehicle Routing Problem with Time Windows (CVRPTW), which we extend by adding intermediate locations for trucks to meet and exchange goods. We illustrate our model for the city of Istanbul using GIS maps, and discuss its various extensions as well as managerial implications.

QoS guarantee with adaptive transmit power and message rate control for DSRC vehicle network based road safety applications

Quality of services (QoS) support is critical for dedicated short range communications (DSRC) vehicle networks based collaborative road safety applications. In this paper we propose an adaptive power and message rate control method for DSRC vehicle networks at road intersections. The design objective is to provide high availability and low latency channels for high priority emergency safety applications while maximizing channel utilization for low priority routine safety applications. In this method an offline simulation based approach is used to find out the best possible configurations of transmit power and message rate for given numbers of vehicles in the network. The identified best configurations are then used online by roadside access points (AP) according to estimated number of vehicles. Simulation results show that this adaptive method significantly outperforms a fixed control method. © 2011 Springer-Verlag.

A new three phase method (SDP method) for the multi-objective vehicle routing problem with simultaneous delvery and pickup (VRPSDP)

Transportation service operators are witnessing a growing demand for bi-directional movement of goods. Given this, the following thesis considers an extension to the vehicle routing problem (VRP) known as the delivery and pickup transportation problem (DPP), where delivery and pickup demands may occupy the same route. The problem is formulated here as the vehicle routing problem with simultaneous delivery and pickup (VRPSDP), which requires the concurrent service of the demands at the customer location. This formulation provides the greatest opportunity for cost savings for both the service provider and recipient. The aims of this research are to propose a new theoretical design to solve the multi-objective VRPSDP, provide software support for the suggested design and validate the method through a set of experiments. A new real-life based multi-objective VRPSDP is studied here, which requires the minimisation of the often conflicting objectives: operated vehicle fleet size, total routing distance and the maximum variation between route distances (workload variation). The former two objectives are commonly encountered in the domain and the latter is introduced here because it is essential for real-life routing problems. The VRPSDP is defined as a hard combinatorial optimisation problem, therefore an approximation method, Simultaneous Delivery and Pickup method (SDPmethod) is proposed to solve it. The SDPmethod consists of three phases. The first phase constructs a set of diverse partial solutions, where one is expected to form part of the near-optimal solution. The second phase determines assignment possibilities for each sub-problem. The third phase solves the sub-problems using a parallel genetic algorithm. The suggested genetic algorithm is improved by the introduction of a set of tools: genetic operator switching mechanism via diversity thresholds, accuracy analysis tool and a new fitness evaluation mechanism. This three phase method is proposed to address the shortcoming that exists in the domain, where an initial solution is built only then to be completely dismantled and redesigned in the optimisation phase. In addition, a new routing heuristic, RouteAlg, is proposed to solve the VRPSDP sub-problem, the travelling salesman problem with simultaneous delivery and pickup (TSPSDP). The experimental studies are conducted using the well known benchmark Salhi and Nagy (1999) test problems, where the SDPmethod and RouteAlg solutions are compared with the prominent works in the VRPSDP domain. The SDPmethod has demonstrated to be an effective method for solving the multi-objective VRPSDP and the RouteAlg for the TSPSDP.

QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.