Extending the solid step fixed-charge transportation problem to consider two-stage networks and multi-item shipments

This paper develops a new mathematical model for a capacitated solid step fixed-charge transportation problem. The problem is formulated as a two-stage transportation network and considers the option of shipping multiple items from the plants to the distribution centers (DC) and afterwards from DCs to customers. In order to tackle such an NP-hard problem, we propose two meta-heuristic algorithms; namely, Simulated Annealing (SA) and Imperialist Competitive Algorithm (ICA). Contrary to the previous studies, new neighborhood strategies maintaining the feasibility of the problem are developed. Additionally, the Taguchi method is used to tune the parameters of the algorithms. In order to validate and evaluate the performances of the model and algorithms, the results of the proposed SA and ICA are compared. The computational results show that the proposed algorithms provide relatively good solutions in a reasonable amount of time. Furthermore, the related comparison reveals that the ICA generates superior solutions compared to the ones obtained by the SA algorithm

A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain

We consider a real-world automobile supply chain in which a first-tier supplier serves an assembler and determines its procurement transport planning for a second-tier supplier by using the automobile assembler's demand information, the available capacity of trucks and inventory levels. The proposed fuzzy multi-objective integer linear programming model (FMOILP) improves the transport planning process for material procurement at the first-tier supplier level, which is subject to product groups composed of items that must be ordered together, order lot sizes, fuzzy aspiration levels for inventory and used trucks and uncertain truck maximum available capacities and minimum percentages of demand in stock. Regarding the defuzzification process, we apply two existing methods based on the weighted average method to convert the FMOILP into a crisp MOILP to then apply two different aggregation functions, which we compare, to transform this crisp MOILP into a single objective MILP model. A sensitivity analysis is included to show the impact of the objectives weight vector on the final solutions. The model, based on the full truck load material pick method, provides the quantity of products and number of containers to be loaded per truck and period. An industrial automobile supply chain case study demonstrates the feasibility of applying the proposed model and the solution methodology to a realistic procurement transport planning problem. The results provide lower stock levels and higher occupation of the trucks used to fulfill both demand and minimum inventory requirements than those obtained by the manual spreadsheet-based method. (C) 2014 Elsevier Inc. All rights reserved.This work has been funded partly by the Spanish Ministry of Science and Technology project: Production technology based on the feedback from production, transport and unload planning and the redesign of warehouses decisions in the supply chain (Ref. DPI2010-19977) and by the Universitat Politecnica de Valencia project 'Material Requirement Planning Fourth Generation (MRPIV) (Ref. PAID-05-12)'.Díaz-Madroñero Boluda, FM.; Peidro Payá, D.; Mula, J. (2014). A fuzzy optimization approach for procurement transport operational planning in an automobile supply chain. Applied Mathematical Modelling. 38(23):5705-5725. https://doi.org/10.1016/j.apm.2014.04.053S57055725382

Solving the Fixed Charge Transportation Problem by New Heuristic Approach

The fixed charge transportation problem (FCTP) is a deployment of the classical transportation problem in which a fixed cost is incurred, independent of the amount transported, along with a variable cost that is proportional to the amount shipped. Since the problem is considered as an NP-hard, the computational time grows exponentially as the size of the problem increases. In this paper, we propose a new heuristic along with well-known metaheuristic like Genetic algorithm (GA), simulated annealing (SA) and recently developed one, Keshtel algorithm (KA) to solve the FCTP. Contrary to previous works, we develop a simple and strong heuristic according to the nature of the problem and compare the result with metaheuristics. In addition, since the researchers recently used the priority-based representation to encode the transportation graphs and achieved very good results, we consider this representation in metaheuristics and compare the results with the proposed heuristic. Furthermore, we apply the Taguchi experimental design method to set the proper values of algorithms in order to improve their performances. Finally, computational results of heuristic and metaheuristics with different encoding approaches, both in terms of the solution quality and computation time, are studied in different problem sizes

Bulk wheat transportation and storage problem of public distribution system

This research investigates the multi-period multi-modal bulk wheat transportation and storage problem in a two-stage supply chain network of Public Distribution System (PDS). The bulk transportation and storage can significantly curtail the transit and storage losses of food grains, which leads to substantial cost savings. A mixed integer non-linear programming model (MINLP) is developed after studying the Indian wheat supply chain scenario, where the objective is to minimize the transportation, storage and operational cost of the food grain incurred for efficient transfer of wheat from producing states to consuming states. The cost minimization of Indian food grain supply chain is a very complex and challenging problem because of the involvement of the many entities and their constraints such as seasonal procurement, limited scientific storages, varying demand, mode of transportation and vehicle capacity constraints. To address this complex and challenging problem of food grain supply chain, we have proposed the novel variant of Chemical Reaction Optimization (CRO) algorithm which combines the features of CRO and Tabu search (TS) and named it as a hybrid CROTS algorithm (Chemical reaction optimization combined with Tabu Search). The numerous problems with different sizes are solved using the proposed algorithm and obtained results have been compared with CRO. The comparative study reveals that the proposed CROTS algorithm offers a better solution in less computational time than CRO algorithm and the dominance of CROTS algorithm over the CRO algorithm is demonstrated through statistical analysis

Uma abordagem para a resolução do problema de transporte com custo fixo

Orientador : Prof. Dr. Arinei Carlos Lindbeck da SilvaCoorientador : Prof. Dr. Gustavo Valentim LochTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Métodos Numéricos em Engenharia. Defesa: Curitiba, 20/06/2017Inclui referências : f. 69-78Resumo: O Problema de Transporte com Custo Fixo (PTCF) é uma classe da Programação Linear (PL), em que o custo total de envio de um produto, de uma origem para um destino, é composto por um custo unitário de transporte, proporcional à quantidade de itens enviados, e um custo fixo, associado à abertura da rota. O PTCF é NP-hard e além disso possui uma característica que à medida que a diferença entre o valor do custo unitário e o do custo fixo aumenta, o tempo computacional sofre alteração, piorando o desempenho. A base de problemas gerada por Sun, em 1998, foi adotada para realizar os testes computacionais. Após revisar alguns métodos da literatura, as heurísticas HEUR-1, HEUR-2, KOWA e HEUR-3 foram desenvolvidas e implementadas, utilizando estrutura de árvores e com otimização em relação ao cálculo das variáveis duais. Após realizar os testes computacionais, os métodos desenvolvidos foram comparados entre si constatando-se a superioridade de HEUR-3. A seguir, HEUR-3 foi comparado com BT, GIP, CORE2 e CORE3, que são métodos da literatura utilizados para resolver o PTCF além de comparar o desempenho com o solver Gurobi. Para todos os testes foi definido como critério de parada o tempo limite de 120 segundos. Cabe ressaltar que HEUR-3 e BT são heurísticas puras enquanto GIP, CORE2 e CORE3 fazem uso de um solver em determinado momento da rotina. Os valores obtidos para o PTCF em cada método da literatura e solver aqui citados, juntamente com HEUR-3, são analisados e discutidos parte a parte. A conclusão dessa tese mostra que HEUR-3 é superior quando comparado ao solver GUROBI e aos métodos BT, CORE2 e CORE3, o que não ocorre apenas com relação à técnica GIP. Palavras-chave: Heurística, implementação computacional, Gurobi.Abstract: The Fixed Charge Transportation Problem (FCTP) is a Linear Programming (LP) class, whereby the total shipping cost of a product, from a source to a destination, consists of a unit transportation cost, proportional to the amount of sent items and a fixed charge associated with the opening of the route. The FCTP is NP-hard and has a characteristic in which, as far as the difference between the value of the unit cost and the fixed charge increases, the computational time changes, worsening the performance. The base of problems generated by Sun, in 1998, was adopted to perform the computational tests. Following the review of some literature methods, the heuristics HEUR-1, HEUR-2, KOWA and HEUR-3 were developed and implemented, using a tree structure and with optimization in relation to the calculation of dual variables. After executing the computational tests, the developed methods were compared to each other, confirming the superiority of HEUR-3. Next, HEUR-3 was compared to BT, GIP, CORE2 and CORE3, which are literature methods used to solve the FCTP, in addition to compare the performance with the Gurobi solver. For all tests, the timeout of 120 seconds was set as stop criterion. It should be noted that HEUR-3 and BT are pure heuristics while GIP, CORE2 and CORE3 make use of a solver at a given moment of the routine. The values obtained for the FCTP in each of the literature methods and solver listed here, together with HEUR-3, are analyzed and discussed side by side. The conclusion of this thesis shows that HEUR-3 is superior when compared to the GUROBI solver and with BT, CORE2 and CORE3 methods, which does not only occur merely to the GIP technique. Keywords: Heuristic, computational implementation, Gurobi