Analysis of hinterland transport strategies when exporting perishable products

Since a good hinterland connection is considered an important factor in port competitiveness, the objective of this paper is to analyse the impact of the development of hinterland transport strategies on the competitiveness of the port by taking the Port of Cape Town, the Republic of South Africa as an example. The development of transport strategies is reflected in terms of a lower cost and higher frequency of inland transport. To investigate the interplay among export products, transport, and access to a port for exporters, we use a linear programming model. The model considers both the choice of transport modes and the impacts of improved inland transport strategies. The model could easily be extended to deal with other modes or transport alternatives. It is assumed that, initially, two modes of transport – trucks and railway − are available for transportation of the export product from the farm to the port. The analysis is extended by including intermodal transportation as a combination of railway and road transport. The results of the analysis show that improving the rail services and offering more frequent rail services from the farm to the port, could lead to a better and more flexible transportation strategy. Keywords: port competitiveness, inland hinterland, dry ports, perishable products, intermodal transport, linear programmingpublishedVersio

An application of the multi-depot heterogeneous fixed fleet open vehicle routing problem

This work describes an application of a multi-depot heterogeneous fixed fleet open vehicle routing problem. A contractor owns a fleet of vehicles with different capacities and running costs. The fleet is used to transport craftsmen from their homes to assigned project sites and back, with some of the craftsmen appointed as drivers while others are passengers. An optimisation model is described that enables the contractor to minimise the transportation costs, and a computational study shows that the model can be solved to optimality for realistically sized instances using a standard mixed-integer programming solver. A variant of the problem is also considered, where the assignment of craftsmen to projects is not fixed a priori. For this variant, several simple heuristic rules are investigated to generate project assignments, and computational results show that they are able to find improved assignments. Keywords: mixed integer programming, assignment, transportationsubmittedVersio

The Value Aspect of Reallocating Seafood Freight from Road to Sea Transport

A case study elaborates on the project organization promoting change of transport mode in a food chain from a value perspective. This project organization may perspectively be viewed as a supply chain with value conceptions different from the everyday seafood supply chain it is meant to develop. Value is in this project context revealed as an intersubjective complex phenomenon, founded in that value conceptions by actors located at different locations in the supply chain. This renders customer value as one of many dynamic value components in this project organization. Value embedded in a supply chain is therefore always a source of uncertainty, a subjective perspective; it cannot be considered as a clear functional purpose in projects aimed at developing food supply. The route to reallocate seafood freight should therefore focus on organizing interconnectivity to support networking and the project members accepting that the project outcome is emergent

Production Planning and Control as Routing in Manufacturing Networks

In this paper, we explore the use of network routing for production planning and control in manufacturing of complex industrial products. Such a product is the result of a joint effort of many manufacturing companies; each considered a collection of work centre nodes connected by transportation links forming a company-wide manufacturing network. Each company is, in turn considered a manufacturing node connected to other manufacturers by transportation links forming a distributed manufacturing network that produces the final product. We model the manufacturing network as a distribution network where the incoming and outgoing inventories of products are distinct nodes in addition to the work centre nodes. Production planning and control are done by minimizing the cost of handling all products in all work centre nodes. This formulation provides a scalable and flexible production planning and control scheme adhering to the networked structure of manufacturing of complex products. We apply the model to a company-wide manufacturing network as a first approach. A case study using the model demonstrates production planning using network routing at a manufacturer of ship propulsion engines

The shrinking and expanding heuristic for the fleet size and mix vehicle routing problem

The FSMVRP (Fleet Size and Mix Vehicle Routing Problem) is a variant of the Classical Capacitated Vehicle Routing Problem, CVRP. We suggest a new methodology, called the Shrinking and Expanding Heuristic (SEH) which is incorporated in a standard tabu search. To determine an appropriate fleet mix is a major challenge in this type of problem and the SEH technique is especially developed to find a good combination of vehicles by introducing a mechanism for changing the existing fleet mix during the search, thus also changing the underlying route structure. The SEH utilizes the concept of depletion and expansion of routes depending upon the filling degree of a vehicle. This strategy is tested on standard problem instances and good quality solutions are obtained.acceptedVersio

A Hybrid approach for milk collection using trucks and trailers

acceptedVersio

The value of integrated planning for production, inventory, and routing decisions: A systematic review and meta-analysis

This paper presents a comparison of sequential and integrated planning for the production routing problem, in which production, inventory, and routing decisions must be made. The aim is to estimate the expected value of treating the problems as a whole, rather than making decisions sequentially. In particular, the following research questions are posed: What is the expected cost reduction when combining production, inventory, and routing in a single modeling framework, compared to solving the problems individually in a sequence? Under which circumstances is it most beneficial to tackle an integrated problem? In other words, the goal is to establish whether the solutions obtained by the integration are clearly better than approximate solutions obtained by a more simplified process, and if so, under which circumstances this difference is the most pronounced. To answer these research questions, a systematic review was performed, resulting in a set of 20 relevant articles that were analyzed in depth. For the first research question, computational results from 15 articles were obtained and analyzed through a meta-analysis. The analysis estimated an expected cost savings provided by integration of 11.08%, with a 95% confidence interval of [6.58%, 15.58%]. For the second research question, individual results obtained via sensitivity analyses in 20 relevant articles were summarized qualitatively, enabling insights into how the potential savings by integration is influenced by parameters such as the degrees of freedom, the cost, and the capacity. © 2022 The AuthorsGrantová Agentura České Republiky, GA ČR; Norges Forskningsråd; Univerzita Tomáše Bati ve Zlíně: GA 20-00091

Quantity-predictive vehicle routing problem for smart waste collection

The current trends in the field of waste management involves the use of modern technologies such as wireless sensors. The smart waste management with Sensor Technology involves an integration of the so-called smart trash bins and containers into existing network by using sensors that fill level of the bins and containers. Apart from the technological aspects of the problem, this arrangement points to the need of development of new decision-making tools that allow collectors to make fast and smart operative decisions on the waste collection. The sensors from the waste containers read the current fill-height once a day and send the information to the central database. The central decision-maker appraises the data and makes the waste collection plan for an entire (e.g., one week) collection period; note that this improves existing models on the data available and used. The aim of this paper is to present complex modelling ideas, develop a simple mathematical model, discuss its complexity and propose/discuss a computational approach in order to solve the collection problem. The objective is to optimize the dynamic planning on daily garbage-truck schedules with respect to minimization of transportation costs that also reflects a positive environmental impact presented by savings in transportation/routing distance. The secondary objective is to optimally decide on early collection of partly-filled containers, especially those directly on or close to the optimum route linking the full ones considering waste production rates in the next days. The paper outlines some directions for further research such as the need of modifying the old-existing models into a form utilizing the newly available data. This leads to specific vehicle routing problems that request appropriate computational time requirements and the need of suitable heuristic methods development. Copyright © 2019, AIDIC Servizi S.r.l