في هذه الصفحة يمكنك الحصول على تحليل مفصل لكلمة أو عبارة باستخدام أفضل تقنيات الذكاء الاصطناعي المتوفرة اليوم:
ألاسم
اِنْدِحار ; اِنْكِسار ; اِنْهِزام ; كَسْرَة ; هَزِيمَة
الفعل
إِبْعاد ; أَجْلَى ; إِفْراد ; إِقْصاء ; تَرْحِيل ; تَغْرِيب ; جَلَا ( عَنْ ) ; دَحَرَ ; دَحْر ; ذَبَّ ; رَحَّلَ ; طَرْد ; عَزْل ; فَصْل ; مُبَاعَدَة ; نَفْي ; هَزَمَ
الصفة
فَلّ ; كَسِير ; مُتَحَطِّم ; مُتَضَعْضِع ; مُتَكَسِّر ; مُتَهَدِّم ; مُتَهَشِّم ; مُحَطَّم ; مَدْحُور ; مَغْلُوب ; مُقَصَّف ; مَقْهُور ; مُكَسَّر ; مَكْسُور ; مَنْقُوض ; مُنْكَسِر ; مُهَدَّم ; مَهْدُود ; هَزِيم
The vehicle routing problem (VRP) is a combinatorial optimization and integer programming problem which asks "What is the optimal set of routes for a fleet of vehicles to traverse in order to deliver to a given set of customers?" It generalises the travelling salesman problem (TSP). It first appeared in a paper by George Dantzig and John Ramser in 1959, in which the first algorithmic approach was written and was applied to petrol deliveries. Often, the context is that of delivering goods located at a central depot to customers who have placed orders for such goods. The objective of the VRP is to minimize the total route cost. In 1964, Clarke and Wright improved on Dantzig and Ramser's approach using an effective greedy algorithm called the savings algorithm.
Determining the optimal solution to VRP is NP-hard, so the size of problems that can be optimally solved using mathematical programming or combinatorial optimization may be limited. Therefore, commercial solvers tend to use heuristics due to the size and frequency of real world VRPs they need to solve.
VRP has many direct applications in industry. Vendors of VRP routing tools often claim that they can offer cost savings of 5%–30%.