Computers and Operations Research
An algorithm for the capacitated, multi-commodity multi-period facility location problem
Computers and Operations Research
On the use of genetic algorithms to solve location problems
Computers and Operations Research - Location analysis
A model and methodologies for the location problem with logistical components
Computers and Operations Research
Supply chain modeling: past, present and future
Computers and Industrial Engineering - Supply chain management
Mathematical Programming: Series A and B
An LP-based heuristic procedure for the generalized assignment problem with special ordered sets
Computers and Operations Research
Dynamic supply chain design with inventory
Computers and Operations Research
Computers and Operations Research
A feasibility pump heuristic for general mixed-integer problems
Discrete Optimization
A property of assignment type mixed integer linear programming problems
Operations Research Letters
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
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We address the problem of designing and planning a multi-period, multi-echelon, multi-commodity logistics network with deterministic demands. This consists of making strategic and tactical decisions: opening, closing or expanding facilities, selecting suppliers and defining the product flows. We use a heuristic approach based on the linear relaxation of the original mixed integer linear problem (MILP). The main idea is to solve a sequence of linear relaxations of the original MILP, and to fix as many binary variables as possible at every iteration. This simple process is coupled with several rounding procedures for some key decision variables. The number of binary decision variables in the resulting MILP is small enough for it to be solved with a solver. The main benefit of this approach is that it provides feasible solutions of good quality within an affordable computation time.