Abstract
In the vehicle routing problem with heterogeneous fleet and variable costs (HFVRP), the group of routes to be developed to satisfy the demand of the customer must be determined, considering the minimization of the total costs of the travelled distance. Heuristic algorithms based on local searches use simple movements (neighborhoods) to generate feasible solutions to problems related to route design. In this article, we conduct a comparative analysis of granular neighborhoods in a Tabu Search for the HFVRP, in terms of the quality of the obtained solution. The computational experiments, performed on instances of benchmarking for the HFVRP, showed the efficiency and effectiveness of implementing some neighborhoods in metaheuristic algorithms of path, such as the Tabu Search.

Abstract
This paper develops a sustainable approach in the productive context associated with the fish industry. The supply network design problem is addressed by using mathematical programming in order to avail the best configuration for the productive system. In this study, some environmental constraints for each echelon have been presented. Two mathematical models are proposed: cost and profit model. The models are validated with actual data obtained from a Colombian fish industry. The obtained results indicate an improved performance of the new supply network design by considering the sustainability approach derived from sustainable supply chain management (SSCM).

Abstract
Dizajn distributivne mreže predstavlja jednu od strateških odluka u konkurenciji za kompanije visokog uticaja. Optimalna lokacija objekata u odnosu na kapacitet ponude i potražnje omogucuje visokom nivou usluga prisustvo na tržištu. U ovom radu predstavljen je metodološki okvir za projektovanje distributivnih mreža kombinovanjem primene tehnika klastera i matematickog programiranja. Predložena metodologija je testirana sa realnim podacima dobijenim od kompanije bezalkoholnih pica u Kolumbiji. Pristup razmatra tri glavne faze. U prvoj fazi, proces klasteriranja kupaca vrši se pomocu K-sredstava kako bi se dobila lokacija za potencijalne distributivne centre (DC). U drugoj fazi, model za dizajn distributivne mreže se vrši pomocu mešovitog programiranja celih brojeva (MPCB) razmatrajuci razlicite opcije za dodeljivanje DC-ma. U finalnoj fazi vrši se procena predložene metodologije u realnom slucaju. Kao rezultat, definisana je distributivna šema koja omogucava ulaz u nova tržišna podrucja sa efikasnom strategijom za prodiranje proizvoda u velike gradove kao što je Bogota u Kolumbiji.

Abstract
This paper considers the problem of allocating vehicles to collect and distribute fruit to producer associations in Colombia. In particular, the problem seeks to determine the optimal allocation of vehicles for fruit collection minimising both total transportation costs and CO2 emissions. This problem has multiple objectives, and the well-known e-constraint method has been used as solution technique for the proposed mathematical models. The efficiency of the former methodology has been tested by using a case study involving the distribution of blackberry (Rubus glaucus) by an association of producers in Cundinamarca Department, Colombia. In particular, we considered 12 different scenarios related to supply levels, route outsourcing, and collection frequency. The results show the efficiency of the proposed methodology in solving vehicle allocation problems related to collection and distribution. The case study reveals that, in general, collecting fruit three days/week yields lower costs and fewer emissions than performing collections four days/week. Furthermore, increased supply leads to greater differences between costs and emissions.