Joint Route Planning under Varying Market Conditions

Purpose - To provide empirical evidence on the level of savings that can be attained by joint route planning and how these savings depend on specific market characteristics.Design/methodology/approach - Joint route planning is a measure that companies can take to decrease the costs of their distribution activities. Essentially, this can either be achieved through horizontal cooperation or through outsourcing distribution to a Logistics Service Provider.The synergy value is defined as the difference between distribution costs in the original situation where all entities perform their orders individually, and the costs of a system where all orders are collected and route schemes are set up simultaneously to exploit economies of scale.This paper provides estimates of synergy values, both in a constructed benchmark case and in a number of real-world cases.Findings - It turns out that synergy values of 30% are achievable.Furthermore, intuition is developed on how the synergy values depend on characteristics of the distribution problem under consideration.Practical implications - The developed intuition on the nature of synergy values can help practitioners to find suitable combinations of distribution systems, since synergy values can quickly be assessed based on the characteristics of the distribution problem, without solving large and difficult Vehicle Routing Problems.Originality/value - this paper addresses a major impediment to horizontal cooperation: estimating operational savings upfront.Horizontal cooperation;Distribution;Outsourcing;Vehicle routing with time windows;Retail

Freight distribution performance indicators for service quality planning in large transportation networks

This paper studies the use of performance indicators in routing problems to estimate how transportation cost is affected by the quality of service offered. The quality of service is assumed to be directly dependent on the size of the time windows. Smaller time windows mean better service. Three performance indicators are introduced. These indicators are calculated directly from the data without the need of a solution method. The introduced indicators are based mainly on a "request compatibility", which describes whether two visits can be scheduled consecutively in a route. Other two indicators are introduced, which get their values from a greedy constructive heuristic. After introducing the indicators, the correlation between indicators and transportation cost is examined. It is concluded that the indicators give a good first estimation on the transportation cost incurred when providing a certain quality of service. These indicators can be calculated easily in one of the first planning steps without the need of a sophisticated solution tool. The contribution of the paper is the introduction of a simple set of performance indicators that can be used to estimate the transportation cost of a routing problem with time window

Improving fleet solution – a case study

Transportation management is a logistical activity with a high impact on a company’s ability to compete in the market. Although the focus on cost reduction is the most usual concern with this activity, lead times and the quality of the service provided should also be considered depending on the market to be served. The goal of this research was to compare different fleet alternatives for a specific construction materials company and discuss which scenario is the most suited to fulfil the company’s customer service policy. A case study approach was developed, and four alternative scenarios were considered. These were compared both regarding the costs they involve, which was analysed using a vehicle routing problem heuristic, and the quality of the customer service they allow, which was assessed based on their ability to provide flexibility in the fleet occupancy rate to respond to unexpected orders. Evidence showed that the current fleet solution is not adequate and investment should be made only if the demand level increases, otherwise outsourcing should be considered along with a minimum level of the self-owned fleet.info:eu-repo/semantics/acceptedVersio

Using the primal-dual interior point algorithm within the branch-price-and-cut method

AbstractBranch-price-and-cut has proven to be a powerful method for solving integer programming problems. It combines decomposition techniques with the generation of both columns and valid inequalities and relies on strong bounds to guide the search in the branch-and-bound tree. In this paper, we present how to improve the performance of a branch-price-and-cut method by using the primal-dual interior point algorithm. We discuss in detail how to deal with the challenges of using the interior point algorithm with the core components of the branch-price-and-cut method. The effort to overcome the difficulties pays off in a number of advantageous features offered by the new approach. We present the computational results of solving well-known instances of the vehicle routing problem with time windows, a challenging integer programming problem. The results indicate that the proposed approach delivers the best overall performance when compared with a similar branch-price-and-cut method which is based on the simplex algorithm

Finding Time Series Discord Based on Bit Representation Clustering

The problem of finding time series discord has attracted much attention recently due to its numerous applications and several algorithms have been suggested. However, most of them suffer from high computation cost and cannot satisfy the requirement of real applications. In this paper, we propose a novel discord discovery algorithm BitClusterDiscord which is based on bit representation clustering. Firstly, we use PAA (Piecewise Aggregate Approximation) bit serialization to segment time series, so as to capture the main variation characteristic of time series and avoid the influence of noise. Secondly, we present an improved K-Medoids clustering algorithm to merge several patterns with similar variation behaviors into a common cluster. Finally, based on bit representation clustering, we design two pruning strategies and propose an effective algorithm for time series discord discovery. Extensive experiments have demonstrated that the proposed approach can not only effectively find discord of time series, but also greatly improve the computational efficiency. © 2013 Elsevier B.V. All rights reserved