Recovery of used products is receiving much attention recently due to growing environmental concern. One of the main difficulties associated with product recovery activities is the degree of uncertainty in terms of ti...
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Recovery of used products is receiving much attention recently due to growing environmental concern. One of the main difficulties associated with product recovery activities is the degree of uncertainty in terms of timing and quantity of returned products. Thus, managing return flow requires a specialised infrastructure and relatively high handling cost and time. For that reason, demand for reverse logistics services from Third Party Reverse Logistics (3PRLs) providers is increasing. Vehicle routing plays a central role in logistics management. The aim of this study is to introduce a heuristic based approach for solving the Vehicle Routing Problem (VRP) of 3PRLs which can be described as the problem of designing optimal routes from one depot to a number of customers subject to constraints.
This paper considers the multi-depot vehicle routing problem(MDVRP),a generalization of the ***- jective of the proposed MDVRP is to minimize the total cost of dispatching cost and traveling *** MDVRP need de- cide th...
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This paper considers the multi-depot vehicle routing problem(MDVRP),a generalization of the ***- jective of the proposed MDVRP is to minimize the total cost of dispatching cost and traveling *** MDVRP need de- cide the route that customer is ***,we use a scatter search(SS)framework to solve MDVRP.A heuristic- based random initialization procedure is developed to generate the diversification solution.A sweep algorithm and the in- sertion heuristic are designed for the improvement and combination method *** result shows that the SS can solve the multi-depot vehicle routing problem effectively.
Driven by the industrial challenge of labeling maps for GIS applications, we investigate the problem of computing the largest convex partitioning of the map P such that the rectangular axis-parallel label L can be pla...
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ISBN:
(纸本)354034070X
Driven by the industrial challenge of labeling maps for GIS applications, we investigate the problem of computing the largest convex partitioning of the map P such that the rectangular axis-parallel label L can be placed in it. The map region to be labeled is in general non-convex and may contain holes. Our main result is the new polygonal area removal (PAR) algorithm to identify the area within P where the center of the label L can be placed. We then derive a new and faster algorithm based on the sweep technique that determines the complete set of maximum inscribed rectangles (MIR) in P in the most common case when rectangle sides have an axis-parallel orientation. The set of all maximum inscribed rectangles is then post-processed to produce the best size/orientation combination of the final label placement depending on the specific requirements from the end users.
The multi-vehicle covering tour problem is defined on a graph G = (V boolean OR W, E), where W is a set of vertices that must collectively be covered by up to in vehicles. The problem consists of determining a set of ...
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The multi-vehicle covering tour problem is defined on a graph G = (V boolean OR W, E), where W is a set of vertices that must collectively be covered by up to in vehicles. The problem consists of determining a set of total minimum length vehicle routes on a subset of V, subject to side constraints, such that every vertex of W is within a prespecified distance from a route. Three heuristics are developed for this problem and tested on randomly generated and real data.
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