A novel multi-objective model for two-echelon green routing problem of perishable products with intermediate depots

In this study, the author focuses on modeling and optimizing a freight routing problem in a road-rail intermodal transportation network that combines the hub-and-spoke and point-to-point structures. The operations of road transportation are time flexible, while rail transportation has fixed departure times. The reliability of the routing is improved by modeling the uncertainty of the road-rail intermodal transportation network. Parameters that are influenced by the real-time status of the network, including capacities, travel times, loading and unloading times, and container trains’ fixed departure times, are considered uncertain in the routing decision-making. Based on fuzzy set theory, triangular fuzzy numbers are employed to formulate the uncertain parameters as well as resulting uncertain variables. Green routing is also discussed by treating the minimization of carbon dioxide emissions as an objective. First of all, a multiobjective fuzzy mixed integer nonlinear programming model is established for the specific reliable and green routing problem. Then, defuzzification, linearization, and weighted sum method are implemented to present a crisp linear model whose global optimum solutions can be effectively obtained by the exact solution algorithm run by mathematical programming software. Finally, a numerical case is given to demonstrate how the proposed methods work. In the case, sensitivity analysis is adopted to reveal the effects of uncertainty on the routing optimization. Fuzzy simulation is then performed to help decision makers to select the best crisp route plan by determining the best confidence level shown in the fuzzy chance constraints.

In actual distribution process, the traffic flow varies with time, and each consumer has multiple fuzzy windows. To minimize the total distribution cost and mean consumer dissatisfaction, this paper sets up a vehicle routing problem (VRP) model with multiple fuzzy time windows, based on time-varying traffic flow. In addition, the Ito algorithm was improved based on time-varying traffic flow. The model and algorithm were verified through example simulation, in comparison with ant colony optimization (ACO). During the simulation, the improved Ito algorithm effectively reduced the distribution cost and consumer dissatisfaction, and outperformed the ACO in solving efficiency and solution quality. The results fully demonstrate the feasibility and effectiveness of the proposed algorithm. The research findings provide a desirable solution to VRPs with multiple fuzzy windows and time-varying traffic flow in the real world.

Automotive industry is very competitive and efficiency is needed in key processes such as logistics in all companies at the supply chain. Using optimization models to increment the efficiency of inbound logistics, such as the in-plant transportation systems, can bring competitive advantages to these companies. This work presents a Vehicle Routing Problem (VRP) model to support and optimize the in-plant transportation system routing, Milk-Run, at the worldwide manufacturing plant of manual assembly in an automotive company, where the routing was planed manually, and too much time and resources were used on this task. At the present, 4 or 5 routes were necessary to supply and collect both raw material and finished items in the plant with 21 workstations. A VRP model was developed into a decision support tool using Integer Programming. The IBM ILOG CPLEX 12.0.8 was used to run the developed model using the production plan of two months of 2018. The results point out an optimal number of 2 milk-runs, a reduction of circa 50%, allowing the freed resources to be used in other production areas of the plant.

In multi-echelon distribution strategy freight is delivered to customers via intermediate depots. Rather than using direct shipments, this strategy is an increasingly popular one in urban logistics. This is primarily to alleviate the environmental (e.g., energy usage and congestion) and social (e.g., traffic-related air pollution, accidents and noise) consequences of logistics operations. This paper represents a two-echelon capacitated vehicle routing problem (2-ECVRP) in which customers' satisfaction and environmental issues are considered for perishable goods delivery for the first time. The paper proposes a novel bi-objective model that minimizes: 1) total customers waiting time, and 2) total travel cost. A restriction on maximum allowable carbon dioxide (CO2) emissions from transport in each route is considered as environmental issue in the problem. The proposed model is solved by simple additive weighting (SAW) method. Finally, the proposed model is applied to a real world problem in a supermarket chain. The results achieved by GAMS optimization software confirm the validity and high performance of the model in respect to the importance of the each objective function. Furthermore, the sensitivity analysis performed on the model reveals that less restrictive policies on carbon emissions lead to more total emissions but less total travel cost and customers waiting time.

The role of sustainability in the function of a company and more specifically a food company is pivotal for its financial performance. The environmental issues as well as the potential economic gains from the implementation of its principles ask for the use of multiple instruments that have been developed to green supply chains. Moreover, social issues also arise and involve the food companies social responsibility, as this can be realized through the supply of fresh products that meet consumption security standards. On this basis, the strategic design of these companies’ supply chains can assists them towards meeting their sustainability objectives as it may lead to the selection of transportation modes, location of entry points and distribution centers, and flows between the nodes of the networks under cost, environmental and social impact minimization criteria. Under this context the purpose of this manuscript is to develop and employ a multi-objective (namely cost, social-time and emission minimization) mixed integer linear programming decision-making model for the network design of sustainable supply chains of perishable food products. The specific model was implemented in the case of a fruits importer in the North-Eastern European region considering its geographical settings. To synopsize and according to our findings the suggested model is an easy to use decision-making tool that leads to a whole set of possible solutions incorporating trade-offs between three aspects of sustainability.

A distribution network design of fast-moving consumer goods ensures distribution of products in an effective manner by giving maximum customers’ satisfaction and minimum distribution cost. The study evaluates the distribution through direct shipment and the use of intermediate shipment for distribution of products from plant to depots. A real-life case study in Southwestern Nigeria was defined and solved as a linear programming model to minimise total cost of distribution from plant to the depots with consideration of four routing options. The results show that distribution through intermediaries gives a better solution than routing option with direct shipment. The best routing option with intermediate points when compared with the routing option with direct shipment gives a savings of 1,819,490.00 Naira which translates to 13.46% cost savings. The study shows that the location of intermediaries is a key decision in distribution network design and that the intermediaries add value to the distribution networks in supply chain.
 Keywords: Distribution network; Supply chain design; Fast-moving consumer goods; Linear programming

Optimization of Chartered Buses Routes Under Uncertainties Using Probabilistic Vehicle Routing Problem Modeling

In order to address the timely delivery of distribution and the internal resource constraints of distribution enterprises, this paper constructed a optimization model of vehicle routing problem (VRP) with multi-constraints, and added test subroutines (such as mileage restrictions, time windows constraints, the number and capacity-limited of vehicles) and an effective mechanism to avoid premature convergence to the ant algorithm to solve the VRP. Finally, a numerical example is presented. Comparison is made between the improved ant algorithm proposed by the paper and saving algorithm, distribution agorithm and genetic algorithm. The experimental results showed that the model and the approach was an effective solution to VRP.

Aiming at the problems of single solution objective in the existing green vehicle routing optimization process and real-time speed change during vehicle travel, a multi-objective green vehicle routing problem with time window constraints in time-varying conditions(MOGVRPTW-TV) is established, then a co-evolutionary framework-based constrained multi-objective evolutionary algorithm for the solving of the model is proposed. First, to better match the actual logistics distribution, this model considers the impact of time-varying speed and capacitated variation on carbon emissions based on capacitated constraints and time window constraints. Second, a constrained multi-objective evolutionary algorithm based on the co-evolutionary framework was proposed for model solving. The algorithm treats the complete problem model as a complex task and introduces a shift crowding distance calculation that considers both individual distribution and convergence information when solving this complex task, effectively balancing the convergence and diversity of solutions. Then, a dynamic constraint selection strategy is designed for the implementation of the simple task, which only considers the effects of some constraints on the populations, and the two populations exchange information through offspring populations to achieve overall optimization. Simulations are performed on different instances and the results show that the proposed algorithm is effective in avoiding traffic congestion periods, decreasing overall distribution costs, and reducing fuel consumption and carbon emissions of vehicles.

Optimal design of the second and third generation biofuel supply network by a multi-objective model

A Novel Matheuristic based on bi-level optimization for the multi-Objective design of hydrogen supply chains

The aim of the paper is to present the research analysis and author’s practical experiences in implementing modern IT solutions. These solutions concern, in particular building and implementing the Integrated Multilevel IT Systems for Logistics, Finance and HR operating in the defense and security services. The detailed research was also on possibility of implementing systems for product coding, electronic shopping and distance learning. Implementing modern IT solutions should improve performance in logistics, finance and HR in defense and security services. The implementation of these solutions in both areas at the same time will be the most effective approach to manage the assets in the most effective way. Implemented IT solutions support rational planning, collecting, storing and using assets. Logistics management should be integrated with finances and Human resources, which facilitates delivery of necessary assets in tight quantity, quality, place and time for competitive price. This will influence achieving set aims (fulfilling tasks) in time of peace, crisis and war. Presented solutions set general directions for informatization and involve implementation of the latest technologies (software, applications, hardware, and computer networks) and IT security. As the result the Integrated Multilevel IT Systems for Logistics, Finance and HR should be built. This system with applied planning, analytical and evaluation applications operates in real time and facilitate information exchange with systems of national economy, NATO and EU. The base of Integrated Multilevel IT Systems for Logistics, Finance and HR is the reliable coding and identification system for all assets used and in stock. With the coding system it is possible to organize electronic shopping which help prevent corruption. The distance learning (e-learning) is another effective solution for logistics, finance and HR. Presented possibilities of implementing new IT solutions for logistics, finance and HR are not the only possibilities new IT solutions offer. The presented ones should serve as an inspiration for decision-makers to further actions, theoretical research and practical steps. The conducted research proved that new IT solutions influence better performance of logistics, finance and HR for defense and security services. It should also be indicated that implementation of new solutions for defense and security services is long organizational and intellectual process. It needs financial means, well prepared experts at single organizational levels where these solutions are being implemented.

Hydrogen supply chain optimization for deployment scenarios in the Midi-Pyrénées region, France

In supply chain management, economical objectives have traditionally guided decisions of the supply chains. However, with increased global environmental and social concerns, in recent years, green aspects have been incorporated in supply chain decisions. These expansions lead to new research areas about green or sustainable supply chain management that includes applying various green practices in order to reduce negative impact on the environment or providing sustainable development. The purpose of this study is to develop a multi-objective optimization model for determining network design of the green supply chains. In multi-objective frame of the proposed model, total profit maximization and environmental impact minimization objectives are considered in order to obtain best network configuration for economic and environmental performance of the green chain. The proposed model is validated with numerical experiments. Obtained results showed that the model can be used as a strategic decision tool in problems with multi and conflicting objectives. Keywords: Green supply chain management, multi-objective modelling, network optimization;

Multi-objective optimization for the deployment of carbon capture utilization and storage supply chain considering economic and environmental performance