Two-stage fuzzy mixed integer optimization model for three-level location allocation problems under uncertain environment

The problem of the optimal three-level location allocation of transfer center, processing factory and distribution center for supply chain network under uncertain transportation cost and customer demand are studied. We establish a two-stage fuzzy 0-1 mixed integer optimization model, by considering the uncertainty of the supply chain. Given the complexity of the model, this paper proposes a modified hybrid second order particle swarm optimization algorithm (MHSO-PSO) to solve the resulting model, yielding the optimal location and maximal expected return of supply chain simultaneously. A case study of clothing supply chain in Shanghai of China is then presented to investigate the specific influence of uncertainties on the transfer center, clothing factory and distribution center three-level location. Moreover, we compare the MHSO-PSO with hybrid particle swarm optimization algorithm and hybrid genetic algorithm, to validate the proposed algorithm based on the computational time and the convergence rate.

An optimization model for selecting wood supply contracts

Procurement for forest companies with pulp and paper mills aims to ensure that a sufficient volume of wood supply enters the production process. Numerous suppliers and contract types are available; however, their selection is a complex decision for procurement managers. In addition, managers typically dedicate a portion of their wood fiber demand to each group of suppliers, which is referred to as a portfolio strategy. Despite the available literature in contract selection, the consideration of contract types and their characteristics have not been addressed for the complex procurement process. In this study, a mixed-integer optimization model is proposed to best select contracts for pulp and paper procurement. The challenge was to plan deliveries in each time period to satisfy the demand of raw material at the mills. The potential of this model is demonstrated with a case study based on characteristics from a forest company in Quebec, Canada. A comparison between traditional fixed and flexible contracts is presented. Different portfolio strategies are also evaluated for groups of suppliers to investigate potential improvements.

Demand Responsive Service-based Optimization on Flexible Routes and Departure Time of Community Shuttles

This paper investigates the optimal routing design problem of a community shuttle system feeding to metro stations based on demand-responsive service. The solution aims to jointly optimize a set of customized routes and the departure time of each route to provide a flexible shuttle service. Considering a set of on-demand trip requests between bus stops and metro stations, a mixed-integer optimization model is formulated to minimize the total system cost, including the operation cost and passenger’s in-vehicle cost, subject to the constraints on the route length, time window, detours, and vehicle capacity. To solve the problem, two metaheuristic algorithms, i.e. a tabu search (TS) and a variable neighborhood search (VNS), with different internal operators are specifically designed. A case study based on a realistic network is conducted to test the model and the solution, and comparisons of the performance of different algorithms are investigated.

Application of a methodology to design a municipal waste pre-collection network in real scenarios

The design of efficient municipal solid waste (MSW) pre-collection networks can contribute to the global efficiency and sustainability of the reverse logistic chain of MSW in modern cities. With this aim, in this paper a comprehensive methodology that involves making decisions in several stages, from waste fraction classification to the final optimization of waste bins’ location, was applied in two real cases of the city of Bahía Blanca, Argentina. This city, does not have much available data about waste generation and, therefore, an important fieldwork had to be performed for applying this methodology, involving estimating population density per block and waste generation rate per inhabitant, identifying the location of commercial and institutional buildings and also estimating its generation rate, as well as performing a characterization of the MSW from similar studies in the literature and surveys performed to make decisions. The modelling of the urban characteristics was performed in a geographic information system. In the bins’ location problem, a mixed-integer optimization model was applied, seeking to minimize the investment costs, given the maximum area available and the capacity of the bins. Different scenarios were analysed, considering different collection frequencies and the maximum distance to be travelled by the user.

Optimal Pump Scheduling for Urban Drainage under Variable Flow Conditions

The paper is focused on the optimal scheduling of a drainage pumping station, complying with variations in the pump rotational speed and a recurrent pattern for the inflow discharge. The paper is structured in several consecutive steps. In the first step, the experimental set-up is described and results of calibration tests on different pumping machines are presented to obtain equations linking significant variables (discharge, head, power, efficiency). Then, those equations are utilized to build a mixed-integer optimization model able to find the scheduling solution that minimizes required pumping energy. The model is solved with respect to a case study referred to a urban drainage system in Naples (Italy) and optimization results are analysed to provide insights on the algorithm computational performance and on the influence of pumping machine characteristics on the overall efficiency savings. With reference to the simulated scenarios, an average value of 32% energy can be saved with an optimized control. Its actual value depends on the hydraulic characteristics of the system.

Towards the Implementation of Optimal Train Loading Plan in the Athens-Thessaloniki Freight Services

The main goal of train loading optimization is the proper assignment of loading units onto the wagons, taking under consideration numerous factors like the maximum axle load restrictions, the condition of the railway infrastructure, the operating conditions, safety regulations etc. The typical expression of the problem is usually formulated under one of the two following assumptions: (a) the commodity load is predefined or (b) the number and type of wagons is fixed. The current work describes the steps that were followed and enabled the analysis, optimization and integration of the train loading plan into the information system that supports the new railway service of TRAINOSE for containers transport on the Athens – Thessaloniki line. This new service, named iCS, was launched in December 2013 and ever since operates on a daily basis. The work includes a literature review, a mention of the pragmatic aspects that influence container transport and train loading plan, the presentation of the heuristic which is implemented in the information system of iCS service, a validation process against a mixed integer optimization model and finally concludes with the proposed solution for the iCS wagon loading problem.

Towards the Implementation of Optimal Train Loading Plan in the Athens-Thessaloniki Freight Services

The main goal of train loading optimization is the proper assignment of loading units onto the wagons, taking under consideration numerous factors like the maximum axle load restrictions, the condition of the railway infrastructure, the operating conditions, safety regulations etc. The typical expression of the problem is usually formulated under one of the two following assumptions: (a) the commodity load is predefined or (b) the number and type of wagons is fixed. The current work describes the steps that were followed and enabled the analysis, optimization and integration of the train loading plan into the information system that supports the new railway service of TRAINOSE for containers transport on the Athens - Thessaloniki line. This new service, named iCS, was launched in December 2013 and ever since operates on a daily basis. The work includes a literature review, a mention of the pragmatic aspects that influence container transport and train loading plan, the presentation of the heuristic which is implemented in the information system of iCS service, a validation process against a mixed integer optimization model and finally concludes with the proposed solution for the iCS wagon loading problem.