Location of municipal waste containers: Trade-off between criteria

There is a growing trend in waste management, which is associated with an increasing number of separately collected waste fractions. This is supported by novel directives of EU, where Circular Economy Package was issued. It presents waste separation and recycling goals, which encourages municipal administrators to support a suitable infrastructure of waste collection points. Such an infrastructure grid should be designed efficiently. There is always a limited number of waste collection points caused by economic reasons. The paper aims to propose a solution to the allocation of waste collection points. It uses different parameters as the decision criteria. These criteria include the volume-weighted walking distance, the number of collection points, the service time of collection vehicle and the total cost of purchasing containers. The problem is formulated through mixed-integer linear programming, and various models are defined as single and multi-objective. The approach is demonstrated in a case study for a municipality in the Czech Republic for plastic waste. The comparison of different approaches is presented by a series of simulations for all defined models. The individual criteria can go against each other in the objective function. The best results are proposed by the model, which minimises the deterioration from optimal values of all criteria. The purchase cost for plastic waste in tested municipality is 23% lower compared with next tested multi-objective model using min-max principle. The better purchase cost is at the expense of walking distance. The difference in walking distance for the two assessed models is 12% per capita. The proposed method serves to stakeholders and municipal administrators to make decisions about the number of containers to purchase and their allocation within an analysed territory for new or already collected waste fractions. [Display omitted] •Holistic multi-objective model for waste bin location is suggested.•Cost and average walking distance were used as allocation decision criteria.•A trade-off between social and economic criteria brings sustainable solution.•The comprehensive case study for plastic revealed optimal criteria weight setting.•New waste streams can be effectively and cost efficiently bin-separated.