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1st May 1970, Page 97
1st May 1970
Page 97
Page 98
Page 97, 1st May 1970 — managernent
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Which of the following most accurately describes the problem?

matters by John Darker, AMBI

Science in transport (4)

The value of operational research

OPERATIONAL RESEARCH has taken a surprisingly long time to make much impact in road transport circles but many of our largest distribution firms are already profiting from OR techniques. It will be some time before all senior transport managers are well versed in the principles of OR; the practice, like that of computer technology, is likely to remain the function of highly trained specialists.

Nevertheless, it is becoming recognized that transport executives who wish to progress ro distribution management must know about the potential usefulness of OR and, in particular, be able to identify the situations in which it alone can provide a satisfactory solution. By the same token, a knowledge of the scope of the supporting services that computers can offer is called for. If distribution management is now "lifting itself by its own boot straps" in management status, as one consultant put it to me, it is only because, in the larger firms, distribution managers are applying themselves to these new aids to management as their brother executives in production and sales did a decade ago.

OR was developed as a tool of government—if not of management—during the 1939-45 war when the spacing of defensive radar stations round the coast of Britain was calculated successfully by mathematical boffins, When Suez was blocked some years ago OR scientists and computer specialists determined the most economical dispositions of bulk tankers on the high seas. Manual calculations would have taken very much longer and would have cost the oil companies vast sums.

The use of critical path techniques—a form of OR—is much used in large building projects. I was interested to examine some of the involved blueprints showing the critical paths—the dates by which various operations needed to be done and the delivery times for materials to the site—at Sainsbury's huge new distribution depot at Charlton, some time ago.

I recently attended a three-day Operational Research course, for transport and distribution managers arranged by the Universities of Lancaster and Sussex, at Windermere. The two universities cooperate closely in the study and practice of OR. Lancaster, in fact, earns many thousands of pounds a year from consultancy fees, and its OR team led by Professor M. G. Simpson, would soon be sadly depleted if earnings from industrial assignments fell off. Very few university departments, I feel, earn their corn as does the OR department of Lancaster University—a clear tribute to the enterprise and skill of its staff.

Vehicle routeing

Professor Simpson's opening lecture "Problems of decision-making and control" contrasted "one off" decisions like the best location for a transport depot, with vehicle routeing programmes, involving the collection and analysis of a vast amount of 'data. He stressed that OR men were not complete problem-solvers; they sought to contribute their special expertise on problems which were, in his words, "decision-sensitive", that is they must matter greatly to an organization. For example, on vehicle routeing, if there were many alternative route-patterns but cost differences were small, this was not a major decision problem.

OR people could often contribute to problem-solving when there was a choice of decisions. To take no action at all was a decision. Sometimes an organization's objectives were not well defined. Differing financial objectives were open to most firms. They could aim to maximize profit or minimize cost—though this rarely amounted to the same thing unless "inputs and outputs" were identical.

Prof Simpson illustrated by describing the dilemma of a company with two courses of action facing a bank closure unless a gross profit of at least £3000 was realized. If course A indicated a 50 per cent chance of a total profit of £5,500 and course B a certain profit of £4,400 the prudent choice, faced with the challenge of the bank, would be to plump for the lower profit. Yet course A, to an entrepreneur, would be more attractive.

Many OR. problems dealt with the effect of changes in service (delivery) times on operating costs. What was the effect on customers if delivery times were lengthened by one or two days? If marked economies were possible such changes in standards of service could be justifiable. Equally, if relatively small and inexpensive changes in operating practice improved customer turnover then this was desirable.

There were limitations sometimes in the capacity of computers to handle problems involving a vast number of variables; for example, which loads should be dispatched from each of many depots in a national distributive network. A special form of mathematics—mathematical programming —could often contribute here. Variability problems such as those met with when a depot platform area was insufficient to cope with peak demands could also be solved—at least the statistical incidence of the resulting congestion, and hence its cost, could be calculated.

Prof, Simpson surprised the students—all senior people in transport and distribution—by saying that in any group of 50 people there would be a common pair of birthdays. Sure enough—in the course of 24 members, two were found with birthdays on the same day in July. One always feels that practitioners of higher mathematics ought to have retired with a fortune before the age of 30 from skill with the horses or the pools1 Fortunately for the science of distribution most OR men devote their talents to practically useful problems.

OR Scientists customarily construct models which simulate real life situations as closely as possible. The models, generally mathematically expressed, include various courses of action as variables. Sometimes the effect of extraneous factors, such as a Budget, are built in. Generally, but not invariably the interconnections between the variables are in mathematical form.

The aim of models is to maximize the "control variables" which maximize the objective sought. A model could be constructed to show the effect of weather on ice' cream distribution, including the number of vehicles necessary, their body size and the appropriate depot locations, having regard to average temperatures and daily hours of sun. Obviously, to obtain useful information by direct experimentation would cost the earth and take years.

Road hauliers or drivers concerned with the all-too-common delays at docks or industrial premises may be comforted to know that a great deal of effort has been expended by OR men on what is known as "queueing theory". Prof. Simpson tended to debunk some of this research work because he pointed out, quite rightly, that the theory really only worked if vehicle arrivals were strictly in random order. In fact, vehicle arrivals are seldom random, for reasons best known to drivers. The proximity of cafes and the time of day contribute to "bunching". Hence, in Prof. Simpson's continued on page 96 view, some of those who spend time on queueing theory produce "lovely elegant maths with no relation to the real world".

However, if "random" meant that vehicles arrived every five minutes on average each hour and the service rate--e.g. refuelling or off-loading—took, say, a constant 10 minutes, then by formula it is possible to calculate the average waiting time of lorries or the waiting time if the service rate was altered. The professor illustrated with graphs how the average waiting time shoots up with random arrivals. Clearly, the moral for road hauliers and drivers is adequate spacing of vehicles. This is very obvious, but not always practised.

OR comes into its own in what may be described as "Total source to destination problems". Prof. Simpson described the classic ,"Biscore" study which related the cost of UK iron-ore imports to unloading efficiency at ports. The study showed it was possible to identify operational costs for various throughputs and it led to further studies, for example by the (then) Steel Company of Wales, who instigated a study to determine the effects of deepening the entrance channel to its ore-port and to assess the maximum potential capacity of the current dock system, in addition to estimating the benefits from increases in unloading rates.

Simulation model A simulation model was constructed which accurately reflected the problem of getting ships of Various sizes over a tide-bar into particular berths and the management of the Steel Company of Wales were presented with a variety of "outputs"—of berth occupancy, queue lengths, turn-round times and despatch bonus earnings, thus providing a meaningful basis for judging the maximum practicable capacity of berths. Similar studies have been done for oil, chemicals and other commodities. The economic case for deep water ports catering for 1000,000-ton or over bulk vessels probably owes much to OR studies.

One fascinating use of OR was by the Douglas Aircraft Corporation who studied in depth the operations of Air Canada and then designed an aircraft to suit the operations. Perhaps there are lessons in this for vehicle manufacturers. Why not a study of brick or timber movement problems with a view to designing special purpose vehicles?

One thing that stands out very clearly is that OR should not be the exclusive domain of university or industrial scientists. The Lancaster University practitioners all stressed the importance of intimate collaboration with practical transport operators. Very ambitious ideas are canvassed by OR men like Prof. Simpson. Summing up in a paper on port operations he stressed that studies hitherto had not really touched the central problem. "Can we use the results of OR models to generate new systems for port dues which would themselves motivate the users to change the system appropriately, and which would not only reduce the total systems costs but would enable each of the parties to get a fair share of the cake?"

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Organisations: Lancaster University

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