Purpose: Aim at choosing a relative good vehicle routing in emergency conditions under constraint conditions when disaster happens. Rapid response and rescue can save a lot of people. Design/methodology/approach: Modeling analysis: establishing a mathematical model of multi-objective emergency...

Purpose: The following investigation aims to deal with the competitive relationship among different warehouses & ports in the same company. Design/methodology/approach: In this paper, Game Theory is used in carrying out the optimization model. Genetic Algorithm is used to solve the model....

Purpose: Integration of various logistical components in supply chain, such as transportation, inventory control and facility location are becoming common practice to avoid suboptimization in nowadays’ competitive environment. The integration of transportation and inventory decisions is known...

Purpose: the distribution routing plans of multi-depots vehicle scheduling problem will increase exponentially along with the adding of customers. So, it becomes an important studying trend to solve the vehicle scheduling problem with heuristic algorithm. On the basis of building the model of...

This paper shows how agent-based stochastic approaches can provide a complementary and more flexible approach to study investment incentives and price dynamics in a real options framework. We particularly study the case of two-stage production chains in which one sector produces an intermediate...

The paper presents a concept and the outline of the implementation of a hybrid approach to modelling and solving constrained problems. Two environments of mathematical programming (in particular, integer programming) and declarative programming (in particular, constraint logic programming) were...

The production and delivery of rapidly perishable goods in distributed supply networks involves a number of tightly coupled decision and optimization problems regarding the just-in-time production scheduling and the routing of the delivery vehicles in order to satisfy strict customer specified...

This study presents the application of strategies of multiobjective differential evolution algorithm (MDEA) to the maximization of irrigation benefit in the lower orange catchment of South Africa. The two strategies presented are MDEA1 and MDEA3 with binomial and exponential crossover methods...

Genetic algorithms are adaptive search methods that simulate some of the natural processes: selection, information, inheritance, random mutation and population dynamics. This paper presents an approach based on genetic algorithm to solve the economic load dispatch (ELD) problem with losses for...

Agent-based models can be manipulated to replicate real- world datasets, but choosing the best set of parameters to achieve this result can be difficult. To validate a model, the real-world dataset is often divided into a training and test set. The training set is used to calibrate the...