WHITE PAPER LAST MILE LOGISTICS
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The evolution of delivery optimization technology
evolve through three
delivery planning
a general rule one skilled planner can manually handle 10-15 routes per day, assuming an average of 40 stops per route. So, hypothetically, a company with 20 dispatch points would need at least one dispatcher per location, plus backup for vacation and abntee relief. And while talented transportation professionals are critically important in the planning process, “throwing people” at the planning issue is quite expensive and does not improve planning effectiveness.
Stage II: “Map on the Computer”
As the first personal computers and rudimentary GIS tools were introduced in the early 1980’s, the ma
p was taken off the wall and put on a computer screen. Pioneering software companies quickly recognized the market opportunity to develop and ll desktop transportation planning packages. Early versions contained lightweight mathematical algorithms and graphical ur interface to produce attractive electronic maps. Certainly, this was an improvement over the manual approach and many organizations embraced the u of technology as an important step forward in route planning.
Many companies using desktop planning software are under the mistaken impression the algorithms imbedded in the software are producing optimized routes. In fact, the vast majority of desktop packages are by design heuristic models that produce “a possible answer among many” – not an optimized solution as the illustration below depicts. Although much better than the manual technique, this approach has two significant shortcomings – simplistic algorithms and limited computing power. Depending on the skill of the ur, and the amount of time available to arch for a better answer (i.e. better = fewer routes and miles), the effort becomes an iterative process to determine the minimum number of routes required to deliver a given workload. In the real world, urs simply do not have the time, computing power or motivation to grind through all the iterations necessary to arrive at an optimum solution.
Further, the decentralized nature of desktop software deployment insures “consistent inconsistency” in applying critical planning parameters. As a result, meaningful comparisons of key operational metrics on an enterpri scale are impossible.
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Stage III: “Centralized Optimization”As the internet era matured in the early 2000’s, the next generation of delivery planning technology began to emerge. Fundamentally different from desktop software, state of the art optimization challenges the conventional wisdom of decentralized deployment. Centralizing the planning process has veral benefits:
• All the critical planning parameters are uniformly and consistently applied to the optimization engine which allows enterpri KPI visibility;
• Advanced mathematical techniques such as integer programming produces far superior results compared to desktop heuristics; and,
• The technology runs in a powerful parallel rver computing environment which reduces the time to find the “best” answer to conds without human intervention.
The operating concept is simple – companies transmit shipment requirements to the centralized data
center via the internet; the optimization engine determines the best solution and transmits back digital maps and stop-by-stop driving directions for each route. New customers are added, scheduled for the appropriate delivery day(s), assigned to the correct route, and inrted into the optimum stop quence.
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Last Mile Logistics
As one would imagine, applying the fundamentally different approaches to the same delivery problem
bushyshould produce vastly different answers. To measure
the magnitude of difference, each approach was tested
with a leading consumer products company delivering
product to residential customers. Company personnel
were already manually planning daily routes so that
approach became the baline for the analysis. To
susx大学ensure “apples-to-apples” comparison, volumes,
coronaviruscustomer locations and delivery constraints were held
constant across the three scenarios. The results are
summarized below:Consumer Products Ca Study
In the United States a typical route cost $125,000
- $150,000 annually to operate (vehicle, driver, fuel
and insurance). Therefore, the business benefit of the
centralized approach is compelling.最新美剧排行榜2013
aestheticallySummary
The cost containment challenge for distribution
intensive companies never really ends. Today the
hot topic is fuel costs; tomorrows may be insurance
premiums, GPS devices or driver compensation.
However, the heart of transportation effectiveness
remains constant – minimizing routes and miles.
Centralized optimization coupled with next generation
technology enables many companies to reduce
transportation costs.About Scientific Logistics, Inc. Scientific Logistics, Inc. offers web-centric optimization technology as a managed rvice to a cross ction of industries. Founded in Atlanta in 2001, the management team has spent the past 30 years developing software to solve complex transportation problems. For more information visit the website m, or contact ron.gable@scientific-
< (706) 247-9893.
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惠灵顿维多利亚大学Below is given annual work summary, do not need friends can download after editor deleted Welcome to visit again
XXXX annual work summary
Dear every leader, colleagues:
Look back end of XXXX, XXXX years of work, have the joy of success in your work, have a collaboration with colleagues, working hard, also have disappointed when encountered difficulties and tbacks. Imperceptible in ten and orderly to be over a year, a year, under the loving care and
重庆朗阁guidance of the leadership of the company, under the support and help of colleagues, through their own efforts, various aspects have made certain progress, better to complete the job. For better work, sum up experience and lessons, will now work a brief summary.
To continuously strengthen learning, improve their comprehensive quality. With good comprehensive quality is the precondition of completes the labor of duty and conditions. A year always put learning in the important position, trying to improve their comprehensive quality. Continuous learning professional skills, learn from surrounding colleagues with rich work experience, equip themlves with knowledge, the expanded aspect of knowledge, efforts to improve their comprehensive quality.
The cond Do best, strictly perform their responsibilities. Set up the company, to maximize the customer to the satisfaction of the company's products, do a good job in technical rvices and product promotion to the company. And collected on the properties of the products of the company, in order to make improvement in time, make the products better meet the using demand of the scene.
Three to learn to be good at communication, coordinating assistance. On‐site technical rvice personnel should not only have strong professional technology, should also have good communicati
on ability, a lot of a product due to improper operation to appear problem, but often not customers reflect the quality of no, so this time we need to find out the crux, and customer communication, standardized operation, to avoid customer's mistrust of the products and even the damage of the company's image. Some experiences in the past work, mentality is very important in the work, work to have passion, keep the smile of sunshine, can clo the distance between people, easy to communicate with the customer. Do better in the daily work to communicate with customers and achieve customer satisfaction, excellent technical rvice every time, on behalf of the customer on our products much a understanding and trust.
Fourth, we need to continue to learn professional knowledge, do practical grasp skilled operation. Over the past year, through continuous learning and fumble, studied the gas generation, collection and methods, gradually familiar with and master the company introduced the working principle, operation method of gas machine. With the help of the department leaders and colleagues, familiar with and master the launch of the division principle, debugging method of the control system, and to wuhan Chen Guchong garbage power plant of gas machine control system transformation, learn to debug, accumulated some experience. All in all, over the past year, did some work, have also made some achievements, but the results can only reprent the past, there are some problems to work, c
an't meet the higher requirements. In the future work, I must develop the onelf advantage, lack of correct, foster strengths and circumvent weakness, for greater achievements. Looking forward to XXXX years of work, I'll be more efforts, constant progress in their jobs, make greater achievements. Every year I have progress, the growth of believe will get greater returns, I will my biggest contribution to the development of the company, believe in yourlf do better next year!
I wish you all work study progress in the year to come.
