Abstract
Marine spatial planning (MSP) has recently attracted more attention as an efficient decision support tool. MSP is a strategic and long-term process gathering multiple competing users of the ocean with the objective to simplify decisions regarding the sustainable use of marine resources. One of the challenges in MSP is to determine an optimal zone to locate a new activity while taking into account the locations of the other existing activities. Most approaches to spatial zoning are formulated as non-linear optimization models involving multiple objectives, which are usually solved using stochastic search algorithms, leading to sub-optimal solutions. In this paper, we propose to model the problem as a Multi-Objective Integer Linear Program. The model is developed for raster data and it aims at maximizing the interest of the area of the zone dedicated to the new activity while maximizing its spatial compactness. We study two resolution methods: first, a weighted-sum of the two objectives, and second, an interactive approach based on an improved augmented version of the ϵ-constraint method, AUGMECON2. To validate and study the model, we perform experiments on artificially generated data. Our experimental study shows that AUGMECON2 represents the most promising approach in terms of relevance and diversity of the solutions, compactness, and computation time.
Highlights
Maritime Spatial Planning (MSP) is to the ocean what land-use planning is to the land: an approach to the organization of activities intended to limit conflicts between actors and activities, promote synergies and minimize environmental impacts
To solve the proposed multi-objective integer linear program, we study in this article two approaches for multi-objective optimization to achieve the appropriate exact Pareto front: first, an a priori method considering the weighted sum of the two objectives as a single objective function, and second, an a posteriori method using an improved version of the classical ǫ-constraint method
Having done all tests concerning validation, sensitivity analysis, and computation time, the main results can be summarized as follows: Validation : (On controlled data) As mentioned before, to prove the validity of the model, we need to show if 100% of the achieved solution is equal to or encompasses the artificially generated best locations of the interest maps by using the controlled random areas
Summary
Maritime Spatial Planning (MSP) is to the ocean what land-use planning is to the land: an approach to the organization of activities intended to limit conflicts between actors and activities, promote synergies and minimize environmental impacts. Each sector developed its own planning, without excessive concern for consistency with the other sectors This is where MSP tries to position itself above these limitations as a systemic approach, whose goal is to plan the human activities in the ocean in a sustainable way, while taking into account interactions between various activities and stakeholders (Agardy, 2015). For a better implementation of MSP, this study deals with the ocean zoning problem for a new human activity This activity takes into account the influence of existing activities occurring in the same marine area and at the same time. The goal of this contribution is to formulate the zoning problem in MSP, to model it through a raster-based Multi-Objective Integer Linear Program (MOILP), and to propose and compare some exact resolution approaches.
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