Location, Routing, and Inventory

Read this article. In it, a model is presented to help determine the number of distribution centers, their locations, and capacity among other factors. Among the 15 assumptions presented, which do you feel are most important and least important?

Problem Formulation

Problem description

The trade-off between cost and time creates a bi-objective problem. One criterion tries to minimize the fixed cost of locating the opened distribution centers, the safety stock costs of distribution center by considering uncertainty in customer's demand, inventory ordering and holding costs, the transportation costs from a plant to its allocated distribution centers, and also vehicle routing costs beginning from a distribution center (DC) with the aim of replying to and covering the devoted customer's demands to the DC by considering risk-pooling. The other criterion looks for the reduction of the time to transport the product along the supply chain. It is desired to minimize the transportation time from a plant to customers. The important assumptions in this paper are as follows:

  1. One kind of product is involved.
  2. Each distribution center j is assumed to follow the (Q_i, R_j) inventory policy.
  3. The inventory control is to be conducted only at DCs in this paper.
  4. A single-sourcing strategy is considered in the whole supply chain.
  5. It is considered that the customers' demands after reaching the retailer are independent and follows a normal distribution.
  6. Each plant has a limited capacity.  
  7. We consider different capacity levels for each distribution center, and finally, one capacity for each of them is selected.
  8. Each DC with the limited capacity carries on-hand inventory to satisfy demands from customer demand zones as well as safety stock to deal with the mutability of the customer demands at customer demand zones to attain risk-pooling profits.
  9. All customers should be served.
  10.  The number of available vehicles for each type and the number of allowed routes for each DC are limited.
  11. There are several modes of transportation between two consecutive levels.
  12. Between two nodes on an echelon, only one type of vehicle is used.
  13. A faster transportation mode is the more expensive one.
  14. The amount of products is transported from each plant to each distribution center that is associated with it, and an equal amount of products has been ordered from the desired distribution center to that plant.
  15. To determine all feasible routes, the following factors are taken into account:
  • Each customer should be visited by only one vehicle.
  • Each route begins at a DC and ends at the same DC.
  • The sum of the demands of the customers served in each route must not exceed the capacity of the associated vehicle.
  • Each of the distribution center and the vehicle have various limited, and determined capacity.

Model formulation

Following are the notations introduced for the mathematical description of the proposed model.

1. Indices

  1.  I, set of plants indexed by i
  2. J, set of candidate DC locations indexed by j
  3. K, set of customer demand zones indexed by k
  4. N_j, set of capacity levels available to DC_j (j ∈ J)
  5. Ω_{jl2}, set of all feasible routes using a vehicle of type l_2 from DC_+{j} (j∈J)
  6. LP_{ij}, set of vehicles l_1 between nodes i and j
  7. LW_{jk}, set of vehicles l_2 between nodes j and k

2. Parameters

  1. F_{j}^{n}, yearly fixed cost for opening and operating distribution center j with capacity level n (∀ n ∈ N_j , ∀ j ∈ J)
  2.  CP_{ijl_1} , cost of transporting one unit of product from plant i to distribution center j using vehicle l_1
  3. CW_{rl_2} , cost of sending one unit of product in route r using vehicle l_2 (These costs include the fixed cost of vehicle plus the transportation cost of each demand unit in route r. The mentioned transportation cost for each demand unit is not related to customer demand zone, and it is considered fixed for all locations in each route r).
  4. TP_{ijl_1}, time for transporting any quantity of a product from plant i to DC_j using vehicle l_1
  5. TW_{jl_2r}, time for transporting any quantity of a product from DC_j on route r using vehicle l_2
  6. λ_j, safety stock factor of DC_j (j ∈ J)
  7. h_j, unit inventory holding cast at DC_j (j ∈ J), (annually)
  8. μ_k, mean demand at customer demand zone k
  9. δ^{2}_{k}, variance of demand at customer demand zone k
  10. E_j, fixed inventory ordering cost at DC_j
  11. b_{j}^{n}, capacity with level n for DC_j
  12. MP_i , capacity of plant i
  13. ω_{l_2}, number of available vehicles of each type l_2
  14. g j , number of routes associated with each distribution center j

3. Binary coefficients

  1. P_{kr}, 1 if and only if customer k is visited by route r, and 0 otherwise

4. Decision variables

  1. U^{n}_{j} , 1 if distribution center j is opened with capacity level n, and 0 otherwise
  2. \(A_{ijl1}, binary variable equal to 1 if vehicle l_1 connecting plant i and DC_j is used, and equal to 0 otherwise
  3. B_jkl_2, binary variable equal to 1 if vehicle l_2 connecting DC_j and customer k is used, and equal to 0 otherwise
  4. X_r , 1 if and only if route r is selected, and 0 otherwise
  5. X_{ijl_1}, quantity transported from plant i to DC_j using vehicle l_1

5. Mathematical model

(a) The problem formulation is as follows:

minf_1 = ∑_{n ∈ N_j} ∑_{j ∈ J} F_{j}^{n} U_{j}^{n} + ∑_{i ∈ I } ∑_{j ∈ J} ∑_{l_1 ∈ LP_{ij}} CP_{ijl_1} A_{ijl_1} X_{ijl_1}

 + ∑_{j ∈ J} ∑_{k ∈ K} ∑_{l_2 ∈ LW_{jk}} ∑_{r ∈ Ω_{jl_2}} CW_{rl_2} μ_k P_{kr} X_r

 +∑_{i ∈ I} ∑_{j ∈  J} ∑_{k ∈ K} ∑_{l_1  ∈ LP_{ij}}  ∑_{l_2}  ∈ LW_{jk} \dfrac{E_j B_{jkl_2 μk}} {X_{ijl_1} A_{ijl_1}}

 +∑_{i ∈ I} ∑_{j ∈ J} ∑_{l_1  ∈ LP_{ij}} \dfrac{A_{ijl1} X_{ijl_1} h_j} {2}

+∑_{j ∈ J} λ_j h_j \sqrt{∑_{i ∈  I} ∑_{k ∈ K} ∑_{l_1 ∈ LP_{ij}} ∑_{l_2 ∈ LW_{jk}} δ_{k}^{2} B_{jkl_2} L_{jil_1} A_{ijl_1}}

min f_2 = max_j (max_{i,l_1} (TP_{ijl_1} A_{ijl_1})+max_{r,l_2} (TW_{jl_2r}X_r))


∑_{n ∈ N_j} U_{j}^{n} ≤ 1 ∀j ∈ J


∑_{k ∈ K} ∑_{l_2 ∈ LW_{jk}} μ_k B_{jkl_2} ≤ ∑_{n ∈ N_j} b_{j}^{n} U_{j}^{n} ∀j ∈ J


∑_{i ∈ I} ∑_{l_1 ∈ LP_{ij}} X_{ijl_1} + λ_{j} \sqrt{∑_{i ∈ I} ∑_{k  ∈ K} ∑_{l_1 ∈ LP_{ij}} ∑_{l_2 ∈ LW_{jk}} δ_{k}^{2} B_{ikl_2} L_{ji l_1} A_{ijl_1}} ≤ ∑_{n ∈ N_j} b_{j}^{n} U_{j}^{n}∀j ∈ J


∑_{j ∈ J} ∑_{l_1 ∈ LP){ij}} X_{ijl_1} ≤ MP_i ∀i ∈ I


 ∑_{i ∈ I} ∑_{l_1 ∈ LP_{ij}} A_{ijl_1} ≥ ∑_{n ∈N_j} U_{j}^{n} ∀j ∈ J


∑_{j ∈ J} ∑_{l_2 ∈ LW_{jk}} B_{jkl_2} =1∀k ∈ K


 ∑_{l_2 ∈ LW_{jk}} B_{jkl_2} ≤ 1∀j ∈ J,∀k ∈ K


 ∑_{l_1 ∈ LP_{ij}} A_{ijl_1} ≤ 1∀i ∈ I,∀j ∈ J


∑_{l_1 ∈ LP_{ij}} ∑_{i ∈ I} A_{ijl_1} ≥ ∑_{l_2 ∈ LW_{jk}} B_{jkl_2} ∀j ∈ J,∀k ∈ K


∑_{n ∈ N_j} U_{j}^{n} ≥ ∑_{l_2 ∈ LW_{jk}} B_{jkl_2}∀j ∈ J,∀k ∈ K


 ∑_{j ∈ J } ∑_{l_2 ∈ LW_{jk}} ∑_{r ∈ Ω_{jl_2}} P_{kr} X_{r} ≥1∀k ∈ K


∑_{j ∈ J} ∑_{r ∈ Ω_jl_2} X_{r} ≤ W_{l_2}∀l_2 ∈ LW_{jk}


∑_{l_2 ∈ LW_{jk}} ∑_{r∈Ω_{jl_2}} X_r ≤ g_{j} ∀j ∈ J

X_{ijl_1} −A_{ijl_1} ≥ 0∀i ∈ I,∀j ∈ J,∀l_1 ∈ LP_{ij}

μk ≥ ∑_{l_2∈LW-_{jk}} ∑_{n ∈ N_j} ∑_{j ∈ J } B_{jk l_2} U_{j}^{n}∀k ∈ K

MP_i−A_{ijl_1} X_{ijl_1} ≥ 0∀i ∈ I,∀j ∈ J,∀l_1 ∈ LP_{ij}

U_{j}^{n} ∈ {0,1} ∀j ∈ J,∀n ∈ N_j

X_r ∈ {0,1} ∀r ∈ ∪ _{j∈J , l_2 ∈LW_{jk}} Ω_{jl_2}

A_{ijl_1} ∈ {0,1} ∀i ∈ I,∀j ∈ J, ∀l_1 ∈ LP_{ij}

B_{jkl_2} ∈ {0,1} ∀j ∈ J,∀k ∈ K,∀l_2 ∈ LW_{jk}

X_{ijl_1} ≻ 0∀i ∈ I,∀j ∈ J,∀l_1∈LP_{ij}

In this model, the first objective function minimizes the total expected costs consisting of the fixed cost for opening distribution centers with a certain capacity level, transportation costs from plants to distribution centers, annual routing costs between distribution centers and customer demand zones, and expected annual inventory costs. The second objective function looks for the minimum time to transport the product along any path from the plants to the customers.

Constraint (1) ensures that each distribution center can be assigned to only one capacity level. Constraints (2) and (3) are the capacity constraints associated with the distribution centers, and also, constraint (4) is the capacity constraints associated with the plants. Constraint (5) states that if distribution center j with n capacity is opened, it is serviced by a plant. Constraint (6) represents the single-sourcing constraints for each customer demand zone. Constraints (7) and (8) ensure that if two nodes on an echelon are related to each other, one type of vehicle transports products between them. Constraint (9) makes sure that if the distribution center j gives the service to the customer k, that center must get services at least from a plant. Constraint (10) ensures that if the distribution center j is allocated to customer k by vehicle l_2, that center should certainly be established with a determined capacity level. Constraint (11) is the standard set covering constraints, modeling assumption 9. Constraints (12) and (13) impose limits on the maximum number of available vehicles of each type and the maximum number of allowed routes for each DC, modeling assumption 10. Constraint (14) makes sure that if plant i gives the service to the DC j , the amount of transported products from that plant to the desired distribution center would be more than one. Constraint (15) implies that customers' demands of zone k are more than 1. Constraint (16) is the capacity constraint associated with plant i. Constraints (17) to (20) enforce the integrality restrictions on the binary variables. Finally, constraint (21) enforces the non-negativity restrictions on the other decision variables.