This paper presents a bi-objective multi-warehouse inventory optimization model for fresh produce, allowing transhipments between warehouses. Initially, we extended our previous proposed mixed-integer quadratic programming model by allowing transhipment between warehouses. Next, we introduce a bi-objective function, as there is a conflict between two cost components: energy cost of warehouses and product deterioration cost. In the bi-objective model, the first objective minimizes energy costs of warehouses, preparation costs of warehouses, inventory holding costs and transhipment costs. The second objective aims to minimize the quantity of deteriorated products. We performed computational experiments using Gurobi optimization using a number of randomly generated instances under three different scenarios based on the value of transhipment costs compared with holding costs (lower, similar or higher). In the first phase of the computational experiments, we consider only transhipments between warehouses (not using the bi-objective function). These results show that considering lateral transhipments decrease the overall costs in all scenarios. Next, we repeat the computational experiments, using the bi-objective function and the transhipment between warehouses. We calculated the weighted sum of both objectives using nine different combinations of weights for the two objective functions testing on the same instances. The resulted pareto fronts provide a decision-making scheme for managers to decide on the best trade-off between warehousing and inventory costs (first objective) and the quantity of deteriorated products (second objective).