SOME OPTIONS FOR MOTOR FREIGHT TRANSPORTATION IN A FUEL CONSTRAINED ENVIRONMENT

Public Economics,

Research of Oil Product Secondary Distribution Optimization Based on Collaborative Distribution

AbstractDuring peak seasons, the petrol company's oil supply capacity is insufficient, therefore, with limited trucks, adjusting the distribution quantity of petrol station and formulating an effective distribution route can minimize the total cost and maximize the vehicle utilization. In this paper we observe the extension of the multi-depot half open vehicle routing problem with time windows (MDHOVRPTW) in oil product secondary distribution. Based on the characteristics of secondary distribution and MDHOVRPTW problem, this paper formulates oil distribution model intra-area with distribution quantity and distribution routing as decision variables. A proposed algorithm is applied to solve this model and result compared with the traditional non-cooperative method to verify the effectiveness of collaborative distribution

Application of multi-agent approach to development of the petrol dispatching system of gas stations network

This work is devoted to questions of analysis, planning and modeling of logistics processes and delivery for oil products supply networks of gas stations. The task of organizing the petroleum product supply process is a complex task of great dimension, which actually comes down to long-term and short-term transportation planning, as well as the operational management of vehicles and the solution of situational management and dispatch tasks. The report discusses the solution of the problem of oil and gas supply to a network of gas stations using a hybrid approach (multi-agent and simulation), as well as its software implementation in the form of a complex decision-making and simulation BPsim. This approach was applied to the "Bashneft"network of petrol stations in the Sverdlovsk Region. © 2020 Published under licence by IOP Publishing Ltd

Optimization Approach for Multi-Period Fuel Replenishment

This paper proposes mathematical models and solution approaches for solving the multi-period fuel replenishment planning problem. The model aims to search for a set of routes, determining the quantity of several petroleum products to be loaded on individual vehicle compartments, and specifying the quantity to be discharged to customer tanks over a given planning horizon in which multiple constraints are satisfied. The objective function is to minimize the transportation unit cost, equal to the total transportation cost divided by the sum of replenished quantity. As the model size grows exponentially when the number of customers, vehicles, and time period increases, an exact algorithm is not feasible. Hence, in this study, we propose two heuristic approaches: two-phase method (2PM) and three-phase method (3PM). The 2PM is primarily designed for solving small problems whereas the 3PM adopts a similar approach but has the ability to solve larger problems. The proposed solutions were tested using a real-life scenario and randomly generated test instance. The results showed that our solution outperforms the solution constructed by experienced planners and also proved that considering multiple periods when devising the fuel replenishment plan, gives superior results in comparison to single periods

Risk based, multi objective vehicle routing problem for hazardous materials: a test case in downstream fuel logistics

Abstract The paper analyses a practical case of study related to the distribution of fuels for the Total Erg Oil Company to the service stations located in the Province of Rome (Italy). The problem is formulated as a capacitated vehicle routing problem with time windows, where several heuristic procedures have been tested, considering both static and dynamic travel times. With respect to the standard operational costs used typically, a multivariable objective function has been proposed which takes into account also a new risk index. The risk index proposed is function of the population density of the zones covered by each path and of the estimated number of road accidents on each road link. In such a way, we take into account the population's exposure to the risk associated with an incidental event involving a fuel tank. The obtained output is the set of planned routes with minimum service cost and minimum risk. Results demonstrate how an accurate planning of the service saves up to 3 hours and 30 km on a daily basis compared to a benchmark. Moreover, the distribution company can parameterize the configuration of the service, by varying the weight adopted in order to include the risk index. Including the risk index may bring to a higher safety route planning, with an increase of the operating costs of only 2%

Advances in operations research models used in the gold mining industry

The topic addressed in this dissertation is a set of economically important operational problems in the gold mining industry that are solved using mathematical models of operations research. More specifically, the main objective of this thesis is to formulate and evaluate decision support models for three important diverse challenges which were found to exist at an underground gold mine in Northwestern Ontario: Newmont Goldcorp’s Red Lake Gold Mine. The challenges discovered at Red Lake Gold Mine are not peculiar to that location but are economically relevant to the underground gold mining industry in as whole. The mine at Red Lake provided a deeper understanding of the problems and data sets. The challenges modeled and solved in this dissertation are: i. minimizing freshwater used in the processing of gold ore; ii. optimizing ore-waste material flow in an underground gold mine; and iii. optimal dispatching of trucks and shovels in an underground gold mine. Each of the three problems was treated with a formulation of the model which is innovative and the evaluation of the results of each case study showed that improved decisions can result when these models are used. This dissertation shows that, for a single gold mine, problems of major economic importance can be found, innovatively modeled, and solved using the methods of operations research. In addition, since these problems are not peculiar to one gold mine, but are found in other gold mines, the innovation of this dissertation is relevant to the underground gold mining industry as a whole and therefore constitutes a minor but important advance in the practical knowledge in this industr

Economic and environmental impacts of collecting waste cooking oil for use as biodiesel under a localized strategy

Some of the vital aspects in the diffusion of renewable energies are the cost of producing the energy, as well as the environmental impacts associated with its lifecycle. As petroleum based energy becomes increasingly costly, alternatives will be relied upon to meet the ever increasing energy demand. Biofuels, and biodiesel in particular, could be a near term solution for providing a transitional fuel to meet the energy demand of the transportation sector. However, the costs of biodiesel, as well as perceptions of a negative energy balance are hindering its widespread adoption. Using waste cooking oil (WCO) can reduce the cost of raw materials necessary for producing biodiesel, when compared to traditional sources, and by collecting and using biodiesel locally, its cost can be further reduced. This research involves the design and development of a simulation model to analyze the costs and emissions associated with waste cooking oil collection for the local, or decentralized, production and use of biodiesel. A case study for the food and beverage industry is investigated. A series of simulation experiments was used to evaluate different scenarios for utilizing the unexploited capacity of a local food and beverage distribution network for the collection of waste cooking oils. The economic and environmental costs associated with collecting WCO were compared to the economic and environmental savings from using biodiesel, the impacts of such operation upon service level are also investigated. Based on the local food and beverage network used to construct the model parameters, biodiesel production from WCO on a localized scale has positive impacts to both cost and emissions without sacrificing customer service